Alternative communication systems for people with severe motor disabilities: a survey
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paper_title: Conception and Experimentation of a Communication Device with Adaptive Scanning

paper_content:

For some people with motor disabilities and speech disorders, the only way to communicate and to have some control over their environment is through the use of a controlled scanning system operated by a single switch. The main problem with these systems is that the communication process tends to be exceedingly slow, since the system must scan through the available choices one at a time until the desired message is reached. One way of raising the speed of message selection is to optimize the elementary scanning delay in real time so that it allows the user to make selections as quickly as possible without making too many errors. With this objective in mind, this article presents a method for optimizing the scanning delay, which is based on an analysis of the data recorded in “log files” while applying the EDiTH system [Digital Teleaction Environment for People with Disabilities]. This analysis makes it possible to develop a human-machine interaction model specific to the study, and then to establish an adaptive algorithm for the calculation of the scanning delay. The results obtained with imposed scenarios and then in ecological situations provides a confirmation that our algorithms are effective in dynamically adapting a scan speed. The main advantage offered by the procedure proposed is that it works on timing information alone and thus does not require any knowledge of the scanning device itself. This allows it to work with any scanning device.
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paper_title: Conception and Experimentation of a Communication Device with Adaptive Scanning

paper_content:

For some people with motor disabilities and speech disorders, the only way to communicate and to have some control over their environment is through the use of a controlled scanning system operated by a single switch. The main problem with these systems is that the communication process tends to be exceedingly slow, since the system must scan through the available choices one at a time until the desired message is reached. One way of raising the speed of message selection is to optimize the elementary scanning delay in real time so that it allows the user to make selections as quickly as possible without making too many errors. With this objective in mind, this article presents a method for optimizing the scanning delay, which is based on an analysis of the data recorded in “log files” while applying the EDiTH system [Digital Teleaction Environment for People with Disabilities]. This analysis makes it possible to develop a human-machine interaction model specific to the study, and then to establish an adaptive algorithm for the calculation of the scanning delay. The results obtained with imposed scenarios and then in ecological situations provides a confirmation that our algorithms are effective in dynamically adapting a scan speed. The main advantage offered by the procedure proposed is that it works on timing information alone and thus does not require any knowledge of the scanning device itself. This allows it to work with any scanning device.
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paper_title: A practical EMG-based human-computer interface for users with motor disabilities

paper_content:

In line with the mission of the Assistive Technology Act of 1998 (ATA), this study proposes an integrated assistive real-time system which "affirms that technology is a valuable tool that can be used to improve the lives of people with disabilities." An assistive technology device is defined by the ATA as "any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities." The purpose of this study is to design and develop an alternate input device that can be used even by individuals with severe motor disabilities. This real-time system design utilizes electromyographic (EMG) biosignals from cranial muscles and electroencephalographic (EEG) biosignals from the cerebrum's occipital lobe, which are transformed into controls for two-dimensional (2-D) cursor movement, the left-click (Enter) command, and an ON/OFF switch for the cursor-control functions. This HCI system classifies biosignals into "mouse" functions by applying amplitude thresholds and performing power spectral density (PSD) estimations on discrete windows of data. Spectral power summations are aggregated over several frequency bands between 8 and 500 Hz and then compared to produce the correct classification. The result is an affordable DSP-based system that, when combined with an on-screen keyboard, enables the user to fully operate a computer without using any extremities.
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paper_title: Geometric optimization of a tongue-operated switch array

paper_content:

An oral tactile interface provides an approach for silent and hands-free communication between humans or between human and machine. An efficient tongue-operated switch array (TOSA), which provides an alternate input or manipulating method for a computer or operative system, is described. A TOSA has been designed and fabricated using printed circuit board technology and a membrane-switching mechanism, and is integrated with a dental palate mold made from a silicone impression material. The TOSA has four switches laid out in cardinal directions with a fifth switch in the center. Human subject experiments have been conducted to evaluate device performance. The characteristics of tactile sensation and mobility of the tongue are used to quantify the performance and optimize the geometric design of the TOSA. Results indicate that operation on all switches are highly accurate and fast enough for use as an alternative input method.
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paper_title: Enhanced hybrid electromyogram/Eye Gaze Tracking cursor control system for hands-free computer interaction.

paper_content:

This paper outlines the development and initial testing of a new hybrid computer cursor control system based on Eye Gaze Tracking (EGT) and electromyogram (EMG) processing for hands-free control of the computer cursor. The ultimate goal of the system is to provide an efficient computer interaction mechanism for individuals with severe motor disabilities (or specialized operators whose hands are committed to other tasks, such as surgeons, pilots, etc.) The paper emphasizes the enhancements that have been made on different areas of the architecture, with respect to a previous prototype developed by our group, and demonstrates the performance improvement verified for some of the enhancements.
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paper_title: Human-machine interface for wheelchair control with EMG and its evaluation

paper_content:

The objective of this paper is to develop a powered wheelchair controller based on EMG for users with high-level spinal cord injury. EMG is very naturally measured when the user indicating a certain direction and the force information which will be used for the speed of wheelchair is easily extracted from EMG. Furthermore, the emergency situation based on EMG will be checked relatively ease. We classified the pre-defined motions such as rest case, forward movement, left movement, and right movement by fuzzy min-max neural networks (FMMNN). This classification results and evaluation results with real users shows the feasibility of EMG as an input interface for powered wheelchair.
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paper_title: EMG signal decomposition: how can it be accomplished and used?

paper_content:

Electromyographic (EMG) signals are composed of the superposition of the activity of individual motor units. Techniques exist for the decomposition of an EMG signal into its constituent components. Following is a review and explanation of the techniques that have been used to decompose EMG signals. Before describing the decomposition techniques, the fundamental composition of EMG signals is explained and after, potential sources of information from and various uses of decomposed EMG signals are described.
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paper_title: Myoelectric Signals for Multimodal Speech Recognition

paper_content:

A Coupled Hidden Markov Model (CHMM) is proposed in this paper to perform multimodal speech recognition using myoeletric signals (MES) from the muscles of vocal articulation. MES signals are immune to noise, and words that are acoustically similar manifest distinctly in MES. Hence, they would effectively complement the acoustic data in a multimodal speech recognition system. Research in Audio-Visual Speech Recognition has shown that CHMMs model the asynchrony between different data streams effectively. Hence, we propose CHMM for multimodal speech recognition using audio and MES as the two data streams. Our experiments indicate that the multimodal CHMM system significantly outperforms the audio only system at different SNRs. We have also provided a comparison between different features for MES and have found that wavelet features provide the best results.
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paper_title: A practical EMG-based human-computer interface for users with motor disabilities

paper_content:

In line with the mission of the Assistive Technology Act of 1998 (ATA), this study proposes an integrated assistive real-time system which "affirms that technology is a valuable tool that can be used to improve the lives of people with disabilities." An assistive technology device is defined by the ATA as "any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities." The purpose of this study is to design and develop an alternate input device that can be used even by individuals with severe motor disabilities. This real-time system design utilizes electromyographic (EMG) biosignals from cranial muscles and electroencephalographic (EEG) biosignals from the cerebrum's occipital lobe, which are transformed into controls for two-dimensional (2-D) cursor movement, the left-click (Enter) command, and an ON/OFF switch for the cursor-control functions. This HCI system classifies biosignals into "mouse" functions by applying amplitude thresholds and performing power spectral density (PSD) estimations on discrete windows of data. Spectral power summations are aggregated over several frequency bands between 8 and 500 Hz and then compared to produce the correct classification. The result is an affordable DSP-based system that, when combined with an on-screen keyboard, enables the user to fully operate a computer without using any extremities.
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paper_title: Multimodal neuroelectric interface development

paper_content:

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.
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paper_title: Neural Control of the Computer Cursor Based on Spectral Analysis of the Electromyogram

paper_content:

A classification algorithm is developed to translate facial movements into five cursor actions: i) left, ii) right, iii) up, iv) down, and v) left-click. The algorithm utilizes the unique spectral characteristics exhibited by electromyogram (EMG) signals obtained from different muscles in the face to assist in the classification process. A previous three-electrode, EMG-based system was utilized in to perform a similar translation of facial movements into cursor actions. This system also made use of spectral analysis to classify muscle activity. It was found that this system does not always discriminate between the EMG activity assigned to up and down cursor actions efficiently. To remedy this matter, a fourth electrode was added and a new classification algorithm was devised. This paper details the classification algorithm utilized with the four-electrode system. It also compares the effectiveness of the four-electrode system to that of the three-electrode system in classifying EMG activity into cursor actions. This was done through the use of Matlab simulations. It will be shown that the new four-electrode system produces significant improvements in classification performance
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paper_title: Can electromyography objectively detect voluntary movement in disorders of consciousness?

paper_content:

Determining conscious processing in unresponsive patients relies on subjective behavioural assessment. Using data from hand electromyography, the authors studied the occurrence of subthreshold muscle activity in response to verbal command, as an objective indicator of awareness in 10 disorders of consciousness patients. One out of eight vegetative state patients and both minimally conscious patients (n = 2) demonstrated an increased electromyography signal specifically linked to command. These findings suggest electromyography could be used to assess awareness objectively in pathologies of consciousness.
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paper_title: Adaptive EMG-driven communication for the disabled

paper_content:

We suggest a communication method for severely disabled persons, who have lost both mobility and speech, and their family using Morse code derived by Masseter muscle EMG. We developed a portable system that comprises EMG amplifier, A/D conversion, text-to-speech module, remote control module and serial communication to the host system. After training, the patient can make speech by composing Morse code by moving his/her chin. Calibration and remote control mode is supported. It also supports the adaptive encoding method for fatigue.
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paper_title: Communication aid for speech disabled people using Morse codification

paper_content:

A synthetic voice aid for speech disabled people is presented in this work. The system is based on the Morse code, given through four keys. A PIC was used to detect and decode Morse code as well as to make the translation to ASCII code. The data processing was performed by an MC68HC11 microcontroller. Voice was generated by a V8600 commercial synthesizer. The aid includes a liquid crystal display for text exhibition, that serves as a feedback reference. The display was mounted on a structure strategically located to avoid interference with the frontal visual field.
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paper_title: Real-time implementation of electromyogram pattern recognition as a control command of man-machine interface.

paper_content:

The purpose of this study was to develop a real-time electromyogram (EMG) discrimination system to provide control commands for man-machine interface applications. A host computer with a plug-in data acquisition and processing board containing a TMS320 C31 floating-point digital signal processor was used to attain real-time EMG classification. Two-channel EMG signals were collected by two pairs of surface electrodes located bilaterally between the sternocleidomastoid and the upper trapezius. Five motions of the neck and shoulders were discriminated for each subject. The zero-crossing rate was employed to detect the onset of muscle contraction. The cepstral coefficients, derived from autoregressive coefficients and estimated by a recursive least square algorithm, were used as the recognition features. These features were then discriminated using a modified maximum likelihood distance classifier. The total response time of this EMG discrimination system was achieved about within 0.17 s. Four able bodied and two C5/6 quadriplegic subjects took part in the experiment, and achieved 95% mean recognition rate in discrimination between the five specific motions. The response time and the reliability of recognition indicate that this system has the potential to discriminate body motions for man-machine interface applications.
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paper_title: A method for evaluating head-controlled computer input devices using Fitts law

paper_content:

The discrete movement task employed in this study consisted of moving a cursor from the center of a computer display screen to circular targets located 24.4 and 110.9 mm in eight radial directions. The target diameters were 2.7, 8.1, and 24.2 mm. Performance measures included movement time, cursor path distance, and root-mean-square cursor deviation. Ten subjects with no movement disabilities were studied using a conventional mouse and a lightweight ultrasonic head-controlled computer input pointing device
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paper_title: Enhanced hybrid electromyogram/Eye Gaze Tracking cursor control system for hands-free computer interaction.

paper_content:

This paper outlines the development and initial testing of a new hybrid computer cursor control system based on Eye Gaze Tracking (EGT) and electromyogram (EMG) processing for hands-free control of the computer cursor. The ultimate goal of the system is to provide an efficient computer interaction mechanism for individuals with severe motor disabilities (or specialized operators whose hands are committed to other tasks, such as surgeons, pilots, etc.) The paper emphasizes the enhancements that have been made on different areas of the architecture, with respect to a previous prototype developed by our group, and demonstrates the performance improvement verified for some of the enhancements.
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paper_title: Development of a hybrid hands-off human computer interface based on electromyogram signals and eye-gaze tracking

paper_content:

A hybrid hands-off human computer interface that uses infrared video eye gaze tracking (EGT) and electromyogram (EMG) signals is introduced. This system combines the advantages of both sub-systems, providing quick cursor displacement In long excursions and steady, accurate movement in small position adjustments. The hybrid system also provides a reliable clicking mechanism. The evaluation protocol used to test the system is described and the results for the hybrid, an EMG Only interface, and the standard hand-held mouse are described and compared. These results show that the hybrid system is, in an average, faster than the EMG-only system by a factor of 2 or more.
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paper_title: A practical EMG-based human-computer interface for users with motor disabilities

paper_content:

In line with the mission of the Assistive Technology Act of 1998 (ATA), this study proposes an integrated assistive real-time system which "affirms that technology is a valuable tool that can be used to improve the lives of people with disabilities." An assistive technology device is defined by the ATA as "any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities." The purpose of this study is to design and develop an alternate input device that can be used even by individuals with severe motor disabilities. This real-time system design utilizes electromyographic (EMG) biosignals from cranial muscles and electroencephalographic (EEG) biosignals from the cerebrum's occipital lobe, which are transformed into controls for two-dimensional (2-D) cursor movement, the left-click (Enter) command, and an ON/OFF switch for the cursor-control functions. This HCI system classifies biosignals into "mouse" functions by applying amplitude thresholds and performing power spectral density (PSD) estimations on discrete windows of data. Spectral power summations are aggregated over several frequency bands between 8 and 500 Hz and then compared to produce the correct classification. The result is an affordable DSP-based system that, when combined with an on-screen keyboard, enables the user to fully operate a computer without using any extremities.
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paper_title: Evaluation of Head Orientation and Neck Muscle EMG Signals as Command Inputs to a Human–Computer Interface for Individuals With High Tetraplegia

paper_content:

We investigated the performance of three user interfaces for restoration of cursor control in individuals with tetraplegia: head orientation, electromyography (EMG) from face and neck muscles, and a standard computer mouse (for comparison). Subjects engaged in a 2-D, center-out, Fitts' Law style task and performance was evaluated using several measures. Overall, head orientation commanded motion resembled mouse commanded cursor motion (smooth, accurate movements to all targets), although with somewhat lower performance. EMG commanded movements exhibited a higher average speed, but other performance measures were lower, particularly for diagonal targets. Compared to head orientation, EMG as a cursor command source was less accurate, was more affected by target direction and was more prone to overshoot the target. In particular, EMG commands for diagonal targets were more sequential, moving first in one direction and then the other rather than moving simultaneous in the two directions. While the relative performance of each user interface differs, each has specific advantages depending on the application.
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paper_title: Application of facial electromyography in computer mouse access for people with disabilities.

paper_content:

Purpose. This study develops a newly facial EMG human – computer interface for people with disabilities for controllng the movement of the cursor on a computer screen.Method. We access the computer cursor according to different facial muscle activity patterns. In order to exactly detect the muscle activity threshold, this study adopts continuous wavelet transformation to estimate the single motor unit action potentials dynamically.Result. The experiment indicates that the accuracy of using the facial mouse is greater than 80%, and this result indicates the feasibility of the proposed system. Moreover, the subject can improve performance of manipulation by repeated training.Conclusion. Compared with previous works, the proposed system achieves complete cursor function and provides an inexpensive solution. Although there are still some drawbacks in the facial EMG-based human – computer interface, the facial mouse can provide an alternative among other expensive and complicated assistive technologies.
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paper_title: A novel position sensors-controlled computer mouse for the disabled

paper_content:

This research reports on the development of a headset-type position sensors-controlled computer mouse for the disabled. This system may serve to assist those who suffer from spinal cord injuries or other handicaps to operate a computer. This system is composed of three major components: (A) the position sensor module; (B) the signal-processing module; and (C) a main controller, the Intel-8951 microprocessor. This concept of design is mainly based on the idea that the use of the position sensor module fastened to the headset could allow the convenient control of the operation of a computer mouse. Through this system, the disabled are competent for some types of work, such as a computer operator. The increase of opportunity to do a job for the disabled would help them live independently.
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paper_title: New classification algorithm for electromyography-based computer cursor control system

paper_content:

At present, a three-input electromyography (EMG) system has been created to provide real-time, hands-free cursor control. The system uses the real-time spectral analysis of three EMG signals to produce the following five cursor actions: i) LEFT, ii) RIGHT, iii) UP, iv) DOWN, v) LEFT-CLICK. The three EMG signals are obtained from two surface electrodes placed on the left and right temples of the head and one electrode placed in the forehead region. The present system for translating EMG activity into cursor actions does not always discriminate between up and down EMG activity efficiently. To resolve this problem it was proposed that the three-electrode system be converted into a four-electrode system, using two electrodes in the forehead of the user, instead of one. This paper compares the effectiveness of the four-electrode system to that of the three-electrode system in classifying EMG activity into cursor actions through the use of Matlab simulations. It will be shown that the new four-electrode system produces significant improvements in classification performance.
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paper_title: Face direction-based human-computer interface using image observation and EMG signal for the disabled

paper_content:

The paralytic caused by the high-level spinal cord injury needs a human-computer interface (HCI) for expressing their intention. In this paper, we propose a novel method to estimate face direction angle using both image observation and electromyogram (EMG) signal from neck muscles. The EMG signal to neck muscle is linear to the face direction angle, but it is undetectable in relatively small angle. Using the image observation, the small face angle is estimated by the geometric relationship between pupils and the face. If two measurements obtained by the EMG signal and the image observation are available, the face direction angle is estimated accurately by a linear interpolation method. We implemented a camera viewing direction control system using the face direction interface, and showed that the proposed method can be used to construct an HCI system for the disabled people with severe motor disabilities.
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paper_title: Design of the human/computer interface for human with disability using myoelectric signal control

paper_content:

The purpose of this study is to develop a human-computer interface (HCI) application based on a real-time EMG discrimination system. A personal computer with a plug-in data acquisition and processing board containing a floating-point digital signal processor are used to attain real-time EMG classification. The integrated EMG is employed to detect the onset of muscle contraction. The cepstral coefficients derived from AR coefficients and estimated by a recursive least square algorithm, are used as the recognition feature. These features are then discriminated using a modified maximum likelihood distance classifier. The identified commands control the mouse cursor. It is fully compatible with a Microsoft serial mouse. This system can move the cursor in four directions, and double-click the icon in GUI operating systems.
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paper_title: Neural Control of the Computer Cursor Based on Spectral Analysis of the Electromyogram

paper_content:

A classification algorithm is developed to translate facial movements into five cursor actions: i) left, ii) right, iii) up, iv) down, and v) left-click. The algorithm utilizes the unique spectral characteristics exhibited by electromyogram (EMG) signals obtained from different muscles in the face to assist in the classification process. A previous three-electrode, EMG-based system was utilized in to perform a similar translation of facial movements into cursor actions. This system also made use of spectral analysis to classify muscle activity. It was found that this system does not always discriminate between the EMG activity assigned to up and down cursor actions efficiently. To remedy this matter, a fourth electrode was added and a new classification algorithm was devised. This paper details the classification algorithm utilized with the four-electrode system. It also compares the effectiveness of the four-electrode system to that of the three-electrode system in classifying EMG activity into cursor actions. This was done through the use of Matlab simulations. It will be shown that the new four-electrode system produces significant improvements in classification performance
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paper_title: Two-Dimensional Cursor-to-Target Control From Single Muscle Site sEMG Signals

paper_content:

In this study, human subjects achieve two-dimensional cursor-to-target control using the surface electromyogram (sEMG) from a single muscle site. The X-coordinate and the Y-coordinate of the computer cursor were simultaneously controlled by the active manipulation of power within two frequency bands of the sEMG power-spectrum. Success of the method depends on the sEMG frequency bandwidths and their midpoints. We acquired the sEMG signals at a single facial muscle site of four able-bodied subjects and trained them, by visual feedback, to control the position of the cursor. After training, all four subjects were able to simultaneously control the X and Y positions of the cursor to accurately and consistently hit three widely-separated targets on a computer screen. This technology has potential application in a wide variety of human-machine interfaces to assistive technologies.
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paper_title: Gazing and frowning as a new human--computer interaction technique

paper_content:

The present aim was to study a new technique for human--computer interaction. It combined the use of two modalities, voluntary gaze direction and voluntary facial muscle activation for object pointing and selection. Fourteen subjects performed a series of pointing tasks with the new technique and with a mouse. At short distances the mouse was significantly faster than the new technique. However, there were no statistically significant differences at medium and long distances between the techniques. Fitts' law analyses were performed both by using only error-free trials and using also data including error trials (i.e., effective target width). In all cases both techniques seemed to follow Fitts' law, although for the new technique the effective target width correlation coefficient was smaller R = 0.776 than for the mouse R = 0.991. The regression slopes suggested that at very long distances (i.e., beyond 800 pixels) the new technique might be faster than the mouse. The new technique showed promising results already after a short practice and in the future it could be useful especially for physically challenged persons.
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paper_title: EMG-Based Speech Recognition Using Hidden Markov Models With Global Control Variables

paper_content:

It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.
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paper_title: Clinical ventilator adjustments that improve speech.

paper_content:

Study objectives: We sought to improve speech in tracheostomized individuals receiving positivepressure ventilation. Such individuals often speak with short phrases, long pauses, and have problems with loudness and voice quality. Subjects: We studied 15 adults with spinal cord injuries or neuromuscular diseases receiving long-term ventilation. Interventions: The ventilator was adjusted using lengthened inspiratory time (TI), positive end-expiratory pressure (PEEP), and combinations thereof. Results: When TI was lengthened (by 8 to 35% of the ventilator cycle), speaking time increased by 19% and pause time decreased by 12%. When PEEP was added (5 to 10 cm H2O), speaking time was 25% longer and obligatory pauses were 21% shorter. When lengthened TI and PEEP were combined (with or without reduced tidal volume), their effects were additive, increasing speaking time by 55% and decreasing pause time by 36%. The combined intervention improved speech timing, loudness, voice quality, and articulation. Individual differences in subject response to the interventions were substantial in some cases. We also tested high PEEP (15 cm H2O) in three subjects and found speech to be essentially identical to that produced with a one-way valve. Conclusions: These simple interventions markedly improve ventilator-supported speech and are safe, at least when used on a short-term basis. High PEEP is a safer alternative than a one-way valve. (CHEST 2003; 124:1512–1521)
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paper_title: Neck and Face Surface Electromyography for Prosthetic Voice Control After Total Laryngectomy

paper_content:

The electrolarynx (EL) is a common rehabilitative speech aid for individuals who have undergone total laryngectomy, but they typically lack pitch control and require the exclusive use of one hand. The viability of using neck and face surface electromyography (sEMG) to control the onset, offset, and pitch of an EMG-controlled EL (EMG-EL) was studied. Eight individuals who had undergone total laryngectomy produced serial and running speech using a typical handheld EL and the EMG-EL while attending to real-time visual sEMG biofeedback. Running speech tokens produced with the EMG-EL were examined for naturalness by 10 listeners relative to those produced with a typical EL using a visual analog scale. Serial speech performance was assessed as the percentage of words that were fully voiced and pauses that were successfully produced. Results of the visual analog scale assessment indicated that individuals were able to use the EMG-EL without training to produce running speech perceived as natural as that produced with a typical handheld EL. All participants were able to produce running and serial speech with the EMG-EL controlled by sEMG from multiple recording locations, with the superior ventral neck or submental surface locations providing at least one of the two best control locations.
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paper_title: Silent speech interfaces

paper_content:

The possibility of speech processing in the absence of an intelligible acoustic signal has given rise to the idea of a 'silent speech' interface, to be used as an aid for the speech-handicapped, or as part of a communications system operating in silence-required or high-background-noise environments. The article first outlines the emergence of the silent speech interface from the fields of speech production, automatic speech processing, speech pathology research, and telecommunications privacy issues, and then follows with a presentation of demonstrator systems based on seven different types of technologies. A concluding section underlining some of the common challenges faced by silent speech interface researchers, and ideas for possible future directions, is also provided.
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paper_title: Session independent non-audible speech recognition using surface electromyography

paper_content:

In this paper we introduce a speech recognition system based on myoelectric signals. The system handles audible and non-audible speech. Major challenges in surface electromyography based speech recognition ensue from repositioning electrodes between recording sessions, environmental temperature changes, and skin tissue properties of the speaker. In order to reduce the impact of these factors, we investigate a variety of signal normalization and model adaptation methods. An average word accuracy of 97.3% is achieved using seven EMG channels and the same electrode positions. The performance drops to 76.2% after repositioning the electrodes if no normalization or adaptation is performed. By applying our adaptation methods we manage to restore the recognition rates to 87.1%. Furthermore, we compare audibly to non-audibly spoken speech. The results suggest that large differences exist between the corresponding muscle movements. Still, our recognition system recognizes both speech manners accurately when trained on pooled data
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paper_title: Myoelectric Signals for Multimodal Speech Recognition

paper_content:

A Coupled Hidden Markov Model (CHMM) is proposed in this paper to perform multimodal speech recognition using myoeletric signals (MES) from the muscles of vocal articulation. MES signals are immune to noise, and words that are acoustically similar manifest distinctly in MES. Hence, they would effectively complement the acoustic data in a multimodal speech recognition system. Research in Audio-Visual Speech Recognition has shown that CHMMs model the asynchrony between different data streams effectively. Hence, we propose CHMM for multimodal speech recognition using audio and MES as the two data streams. Our experiments indicate that the multimodal CHMM system significantly outperforms the audio only system at different SNRs. We have also provided a comparison between different features for MES and have found that wavelet features provide the best results.
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paper_title: Speech recognition as a function of channel capacity in a discrete set of channels.

paper_content:

There have been many attempts to perform a frequency analysis of speech and to use the outputs of this analysis to provide cutaneous stimulation. The results of these tests have left in doubt the issue of whether or not cutaneous recognition of speech is actually possible. In addition to other difficulties, an optimum frequency analysis has never been achieved. Instead, filtering configurations have been chosen essentially arbitrarily. The systems considered may well have had insufficient channel capacity for speech recognition even in the event that the tactile stimulators were arranged in an optimum manner. In this paper, several sets of finite frequency band to discrete channels filters were considered. The frequency of each discrete channel was constrained to the fixed center frequency of the corresponding band so as to be directly translatable to the position of a tactile stimulator. Tests were conducted to measure the auditory recognition rate of speech, resynthesized as the sum of these discrete ch...
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paper_title: Electrode position optimization for facial EMG measurements for human-computer interface

paper_content:

The aim of this work was to model facial electromyography (fEMG) to find optimal electrode positions for wearable human-computer interface system. The system is a head cap developed in our institute and with it we can measure fEMG and electro-oculogram (EOG). The signals can be used to control the computer interface: gaze directions move the cursor and muscle activations correspond to clicking. In this work a very accurate 3D model of the human head was developed and it was used in the modeling of fEMG. The optimal positions of four electrodes on the forehead measuring the activations of frontalis and corrugator muscles were defined. It resulted that the electrode pairs used in frontalis and corrugator measurements should be placed orthogonally by comparison with each other to get a signal that enables the separation of those two different activations.
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paper_title: Multi-stream HMM for EMG-based speech recognition

paper_content:

A technique for improving the recognition accuracy of EMG-based speech recognition by applying existing speech recognition technologies is proposed. The authors have proposed an EMG-based speech recognition system that requires only mouth movements, voice need not be generated. A multi-stream HMM (hidden Markov model) and feature extraction technique are applied to EMG-based speech recognition. 3 channel facial EMG signals are collected from ten subjects when uttering 10 Japanese isolated digits. One channel corresponds to one stream. By examining various features, we found that the delta component of the static parameter leads to higher accuracy. Compared to equal stream weighting, the individual optimization of stream weights increased recognition accuracy by 4.0% which corresponds to a 12.8% reduction in error rate. This result shows that multistream HMM is effective for the classification of EMG.
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paper_title: EMG based voice recognition

paper_content:

Besides its clinical applications, various researchers have shown that EMG can be utilised in areas such as computer human interface and in developing intelligent prosthetic devices. The paper presents results from a preliminary study. The work describes the outcome in using an artificial neural network (ANN) to recognise and classify human speech based on EMG. The EMG signals were acquired from three articulatory facial muscles. Three subjects were selected and participated in the experiments. Preliminarily, five English vowels were used as recognition variables. The root mean square (RMS) values of the EMG signals were estimated and used as a set of features to feed the ANN. The findings indicate that such a system may have the capacity to recognise and classify speech signals with an accuracy of up to 88%.
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paper_title: Design of an Electroocular Computing Interface

paper_content:

The human retina consists of an electrically-charged nerve membrane. This potential is a constant value for a given adaptation without stimulation; it is the retinal resting potential. The retinal resting potential causes an electric field around the eyeball, centered on the optical axis, which can be measured by placing electrodes near to the eye. As a result, the motion of the eye causes a measurable change of DC voltage between the surface electrodes. The same vector coordinate system employed in the modern computer mouse may be adapted for use with our electro-ocular interface. Such a device would provide a relative position of gaze and have application in both hands-busy and assistive research. The theory behind our device, hardware design, the experimental results, and efficacy of the system are presented.
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paper_title: Implementation of the EOG-Based Human Computer Interface System

paper_content:

Bio-based human computer interface(HCI) has attracted more and more attention of researches all over the world in recent years. In this paper, an EOG-based HCI system is introduced. It is composed of three parts: EOG amplifying and acquisition, EOG pattern recognition and control command output. Three plane electrodes are employed to detects the EOG signals, which contains the information related to the eye blinking and vertical( or horizontal ) eye movements referred to pre-designed command table. An online signal processing algorithm is designated to get the command information contained in EOG signals, and these commands could be used to control the computer or other instruments. Based on this HCI system, the remote control experiments driven by EOG are realized.
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paper_title: A Practical Biosignal-Based Human Interface Applicable to the Assistive Systems for People with Motor Impairment

paper_content:

An alternative human interface enabling the handicapped with severe motor disabilities to control an assistive system is presented. Since this interface relies on the biosignals originating from the contraction of muscles on the face during particular movements, even individuals with a paralyzed limb can use it with ease. For real-world application, a dedicated hardware module employing a general-purpose DSP was implemented and its validity tested on an electrically powered wheelchair. Furthermore, an additional attempt to reduce error rates to a minimum for stable operation was also made based on the entropy information inherent in the signals during the classification phase. In the experiments in which 11 subjects participated, it was found most of them could control the target system at their own will, and thus the proposed interface could be considered a potential alternative for the interaction of the severely handicapped with electronic systems.
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paper_title: EOG and EMG based virtual keyboard: A brain-computer interface

paper_content:

This paper discusses a brain-computer interface through electrooculogram (EOG) and electromyogram (EMG) signals. In situations of disease or trauma, there may be inability to communicate with others through means such as speech or typing. Eye movement tends to be one of the last remaining active muscle capabilities for people with neurodegenerative disorders, such as amyotrophic lateral sclerosis (ALS) also known as Lou Gehrig's disease. Thus, there is a need for eye movement based systems to enable communication. To meet this need, we proposed a system to accept eye-gaze controlled navigation of a particular letter and EMG based click to enter the letter. Eye -gaze direction (angle) is obtained from EOG signals and EMG signal is recorded from eyebrow muscle activity. A virtual screen keyboard may be used to examine the usability of the proposed system.
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paper_title: Eye Movement-Based Human-Computer Interaction Techniques: Toward Non-Command Interfaces

paper_content:

User-computer dialogues are typically one-sided, with the bandwidth from computer to user far greater than that from user to computer. The movement of a user’s eyes can provide a convenient, natural, and high-bandwidth source of additional user input, to help redress this imbalance. We therefore investigate the introduction of eye movements as a computer input medium. Our emphasis is on the study of interaction techniques that incorporate eye movements into the user-computer dialogue in a convenient and natural way. This chapter describes research at NRL on developing such interaction techniques and the broader issues raised by non-command-based interaction styles. It discusses some of the human factors and technical considerations that arise in trying to use eye movements as an input medium, describes our approach and the first eye movement-based interaction techniques that we have devised and implemented in our laboratory, reports our experiences and observations on them, and considers eye movement-based interaction as an exemplar of a new, more general class of non-command-based user-computer interaction.
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paper_title: Drifting and Blinking Compensation in Electro-oculography (EOG) Eye-gaze Interface

paper_content:

This paper describes an eye-gaze interface using a biological signal, electro-oculorgram (EOG). This interface enables a user to move a computer cursor on a graphical user interface using eye gaze movement alone. It will be useful as a communication aid for individuals with mobility handicaps. Although EOG is easily recordable, drifting and blinking problems must be solved to produce a reliable eye-gaze interface. Here we introduced a calibration method and a feedback control to overcome these problems.
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paper_title: Development of human-mobile communication system using electrooculogram signals

paper_content:

Present the development of a human-mobile robot communication system using electrooculogram (EOG) signals. An ideal velocity shape signal processing algorithm is proposed to extract position data where the eyes are focusing on from the noise and drift included in EOG signals. Additionally, an efficient algorithm for the detection of various eye-lip movements such as blink and wink is suggested. Two experiments were performed for the validation of the human-mobile communication system. One is point stabilization of a mobile robot, using extracted eye focusing position data. The other is a moving target following experiment using various eye-lip movements as mobile robot commands.
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paper_title: Wheelchair Guidance Strategies Using EOG

paper_content:

This paper describes an eye-control method, based on electrooculography (EOG), for guiding and controlling a wheelchair for disabled people; the control is actually effected by eye movements within the socket. An eye model based on an electrooculographic signal is proposed and its validity is studied. Different techniques and guidance strategies are then shown with comments on the advantages and disadvantages of each one. The system consists of a standard electric wheelchair with an on-board computer, sensors and a graphic user interface run by the computer. This control technique could be useful in multiple applications, such as mobility and communication aid for handicapped persons.
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paper_title: System for assisted mobility using eye movements based on electrooculography

paper_content:

This paper describes an eye-control method based on electrooculography (EOG) to develop a system for assisted mobility. One of its most important features is its modularity, making it adaptable to the particular needs of each user according to the type and degree of handicap involved. An eye model based on electroculographic signal is proposed and its validity is studied. Several human-machine interfaces (HMI) based on EOG are commented, focusing our study on guiding and controlling a wheelchair for disabled people, where the control is actually effected by eye movements within the socket. Different techniques and guidance strategies are then shown with comments on the advantages and disadvantages of each one. The system consists of a standard electric wheelchair with an on-board computer, sensors and a graphic user interface run by the computer. On the other hand, this eye-control method can be applied to handle graphical interfaces, where the eye is used as a mouse computer. Results obtained show that this control technique could be useful in multiple applications, such as mobility and communication aid for handicapped persons.
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paper_title: Development of communication supporting device controlled by eye movements and voluntary eye blink

paper_content:

A communication support interface controlled by eye movements and voluntary eye blink has been developed for disabled individuals with motor paralysis who cannot speak. Horizontal and vertical electro-oculograms were measured using two surface electrodes attached above and beside the dominant eye and referring to an earlobe electrode and amplified with AC-coupling in order to reduce the unnecessary drift. Four directional cursor movements ---up, down, right, and left--- and one selected operation were realized by logically combining the two detected channel signals based on threshold settings specific to the individual. Letter input experiments were conducted on a virtual screen keyboard. The method's usability was enhanced by minimizing the number of electrodes and applying training to both the subject and the device. As a result, an accuracy of 90.1 ± 3.6% and a processing speed of 7.7 ± 1.9 letters/min. were obtained using our method.
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paper_title: Implementation of the EOG-Based Human Computer Interface System

paper_content:

Bio-based human computer interface(HCI) has attracted more and more attention of researches all over the world in recent years. In this paper, an EOG-based HCI system is introduced. It is composed of three parts: EOG amplifying and acquisition, EOG pattern recognition and control command output. Three plane electrodes are employed to detects the EOG signals, which contains the information related to the eye blinking and vertical( or horizontal ) eye movements referred to pre-designed command table. An online signal processing algorithm is designated to get the command information contained in EOG signals, and these commands could be used to control the computer or other instruments. Based on this HCI system, the remote control experiments driven by EOG are realized.
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paper_title: A low-cost interface for control of computer functions by means of eye movements

paper_content:

Human-computer interactions (HCI) have become an important area of research and development in computer science and psychology. Appropriate use of computers could be of primary importance for communication and education of those subjects which could not move, speak, see or hear properly. The aim of our study was to develop a reliable, low-cost and easy-to-use HCI based on electrooculography signal analysis, to allow physically impaired patients to control a computer as assisted communication. Twenty healthy subjects served as volunteers: eye movements were captured by means of four electrodes and a two-channel amplifier. The output signal was then transmitted to an ''Analog to Digital'' (AD) converter, which digitized the signal of the amplifier at a rate of 500Hz, before being sent to a laptop. We designed and coded a specific software, which analyzed the input signal to give an interpretation of eye movements. By means of a single ocular movement (up, down, left and right) the subjects were then able to move a cursor over a screen keyboard, passing from one letter to another; a double eye blink was then necessary to select and write the active letter. After a brief training session, all the subjects were able to confidently control the cursor and write words using only ocular movements and blinking. For each subject we presented three series of randomized words: mean time required to enter a single character was about 8.5s, while input errors were very limited (less than 1 per 250 characters). Our results confirm those obtained in previous studies: eye-movement interface can be used to properly control computer functions and to assist communication of movement-impaired patients.
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paper_title: Development of EOG-Based Communication System Controlled by Eight-Directional Eye Movements

paper_content:

A communication support interface controlled by eye movements and voluntary eye blink has been developed for disabled individuals with motor paralysis who cannot speak. Horizontal and vertical electro-oculograms were measured using two electrodes attached above and beside the dominant eye and referring to an earlobe electrode and amplified with AC-coupling in order to reduce the unnecessary drift. Eight directional cursor movements and one selected operation were realized by logically combining the two detected channel signals based on threshold setting specific to the individuals. As experimental results using a projected screen keyboard, processing speed was improved to 12.1 letters/min. while the accuracy was 90.4%.
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paper_title: Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans

paper_content:

Brain-computer interfaces (BCIs) can provide communication and control to people who are totally paralyzed. BCIs can use noninvasive or invasive methods for recording the brain signals that convey the user's commands. Whereas noninvasive BCIs are already in use for simple applications, it has been widely assumed that only invasive BCIs, which use electrodes implanted in the brain, can provide multidimensional movement control of a robotic arm or a neuroprosthesis. We now show that a noninvasive BCI that uses scalp-recorded electroencephalographic activity and an adaptive algorithm can provide humans, including people with spinal cord injuries, with multidimensional point-to-point movement control that falls within the range of that reported with invasive methods in monkeys. In movement time, precision, and accuracy, the results are comparable to those with invasive BCIs. The adaptive algorithm used in this noninvasive BCI identifies and focuses on the electroencephalographic features that the person is best able to control and encourages further improvement in that control. The results suggest that people with severe motor disabilities could use brain signals to operate a robotic arm or a neuroprosthesis without needing to have electrodes implanted in their brains.
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paper_title: Two-dimensional movement control using electrocorticographic signals in humans

paper_content:

We show here that a brain-computer interface (BCI) using electrocorticographic activity (ECoG) and imagined or overt motor tasks enable humans to control a computer cursor in two dimensions. Over a brief training period of 12-36 min, each of five human subjects acquired substantial control of particular ECoG features recorded from several locations over the same hemisphere, and achieved average success rates of 53-73% in a two-dimensional four-target center-out task in which chance accuracy was 25%. Our results support the expectation that ECoG-based BCIs can combine high performance with technical and clinical practicality, and also indicate promising directions for further research.
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paper_title: Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials

paper_content:

Abstract This paper describes the development and testing of a system whereby one can communicate through a computer by using the P300 component of the event-related brain potential (ERP). Such a system may be used as a communication aid by individuals who cannot use any motor system for communication (e.g., ‘locked-in’ patients). The 26 letters of the alphabet, together with several other symbols and commands, are displayed on a computer screen which serves as the keyboard or prosthetic device. The subject focuses attention successively on the characters he wishes to communicate. The computer detects the chosen character on-line and in real time. This detection is achieved by repeatedly flashing rows and columns of the matrix. When the elements containing the chosen character are flashed, a P300 is elicited, and it is this P300 that is detected by the computer. We report an analysis of the operating characteristics of the system when used with normal volunteers, who took part in 2 experimental sessions. In the first session (the pilot study/training session) subjects attempted to spell a word and convey it to a voice synthesizer for production. In the second session (the analysis of the operating characteristics of the system) subjects were required simply to attend to individual letters of a word for a specific number of trials while data were recorded for off-line analysis. The analyses suggest that this communication channel can be operated accurately at the rate of 0.20 bits/sec. In other words, under the conditions we used, subjects can communicate 12.0 bits, or 2.3 characters, per min.
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paper_title: Study of discriminant analysis applied to motor imagery bipolar data

paper_content:

We present a study of linear, quadratic and regularized discriminant analysis (RDA) applied to motor imagery data of three subjects. The aim of the work was to find out which classifier can separate better these two-class motor imagery data: linear, quadratic or some function in between the linear and quadratic solutions. Discriminant analysis methods were tested with two different feature extraction techniques, adaptive autoregressive parameters and logarithmic band power estimates, which are commonly used in brain–computer interface research. Differences in classification accuracy of the classifiers were found when using different amounts of data; if a small amount was available, the best classifier was linear discriminant analysis (LDA) and if enough data were available all three classifiers performed very similar. This suggests that the effort needed to find regularizing parameters for RDA can be avoided by using LDA.
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paper_title: EEG-based neuroprosthesis control: A step towards clinical practice

paper_content:

Abstract This case study demonstrates the coupling of an electroencephalogram (EEG)-based Brain–Computer Interface (BCI) with an implanted neuroprosthesis (Freehand ® system). Because the patient was available for only 3 days, the goal was to demonstrate the possibility of a patient gaining control over the motor imagery-based Graz BCI system within a very short training period. By applying himself to an organized and coordinated training procedure, the patient was able to generate distinctive EEG-patterns by the imagination of movements of his paralyzed left hand. These patterns consisted of power decreases in specific frequency bands that could be classified by the BCI. The output signal of the BCI emulated the shoulder joystick usually used, and by consecutive imaginations the patient was able to switch between different grasp phases of the lateral grasp that the Freehand ® system provided. By performing a part of the grasp-release test, the patient was able to move a simple object from one place to another. The results presented in this work give evidence that Brain–Computer Interfaces are an option for the control of neuroprostheses in patients with high spinal cord lesions. The fact that the user learned to control the BCI in a comparatively short time indicates that this method may also be an alternative approach for clinical purposes.
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paper_title: Brain–computer interfaces as new brain output pathways

paper_content:

Brain–computer interfaces (BCIs) can provide non-muscular communication and control for people with severe motor disabilities. Current BCIs use a variety of invasive and non-invasive methods to record brain signals and a variety of signal processing methods. Whatever the recording and processing methods used, BCI performance (e.g. the ability of a BCI to control movement of a computer cursor) is highly variable and, by the standards applied to neuromuscular control, could be described as ataxic. In an effort to understand this imperfection, this paper discusses the relevance of two principles that underlie the brain's normal motor outputs. The first principle is that motor outputs are normally produced by the combined activity of many CNS areas, from the cortex to the spinal cord. Together, these areas produce appropriate control of the spinal motoneurons that activate muscles. The second principle is that the acquisition and life-long preservation of motor skills depends on continual adaptive plasticity throughout the CNS. This plasticity optimizes the control of spinal motoneurons. In the light of these two principles, a BCI may be viewed as a system that changes the outcome of CNS activity from control of spinal motoneurons to, instead, control of the cortical (or other) area whose signals are used by the BCI to determine the user's intent. In essence, a BCI attempts to assign to cortical neurons the role normally performed by spinal motoneurons. Thus, a BCI requires that the many CNS areas involved in producing normal motor actions change their roles so as to optimize the control of cortical neurons rather than spinal motoneurons. The disconcerting variability of BCI performance may stem in large part from the challenge presented by the need for this unnatural adaptation. This difficulty might be reduced, and BCI development might thereby benefit, by adopting a ‘goal-selection’ rather than a ‘process- control’ strategy. In ‘process control’, a BCI manages all the intricate high-speed interactions involved in movement. In ‘goal selection’, by contrast, the BCI simply communicates the user's goal to software that handles the high–speed interactions needed to achieve the goal. Not only is ‘goal selection’ less demanding, but also, by delegating lower-level aspects of motor control to another structure (rather than requiring that the cortex do everything), it more closely resembles the distributed operation characteristic of normal motor control.
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paper_title: Nessi: An EEG-Controlled Web Browser for Severely Paralyzed Patients

paper_content:

We have previously demonstrated that an EEG-controlled web browser based on self-regulation of slow cortical potentials (SCPs) enables severely paralyzed patients to browse the internet independently of any voluntary muscle control. However, this system had several shortcomings, among them that patients could only browse within a limited number of web pages and had to select links from an alphabetical list, causing problems if the link names were identical or if they were unknown to the user (as in graphical links). Here we describe a new EEG-controlled web browser, called Nessi, which overcomes these shortcomings. In Nessi, the open source browser, Mozilla, was extended by graphical in-place markers, whereby different brain responses correspond to different frame colors placed around selectable items, enabling the user to select any link on a web page. Besides links, other interactive elements are accessible to the user, such as e-mail and virtual keyboards, opening up a wide range of hypertext-based applications.
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paper_title: Bipolar electrode selection for a motor imagery based brain?computer interface

paper_content:

A motor imagery based brain?computer interface (BCI) provides a non-muscular communication channel that enables people with paralysis to control external devices using their motor imagination. Reducing the number of electrodes is critical to improving the portability and practicability of the BCI system. A novel method is proposed to reduce the number of electrodes to a total of four by finding the optimal positions of two bipolar electrodes. Independent component analysis (ICA) is applied to find the source components of mu and alpha rhythms, and optimal electrodes are chosen by comparing the projection weights of sources on each channel. The results of eight subjects demonstrate the better classification performance of the optimal layout compared with traditional layouts, and the stability of this optimal layout over a one week interval was further verified.
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paper_title: Event-related EEG/MEG synchronization and desynchronization: basic principles

paper_content:

Abstract An internally or externally paced event results not only in the generation of an event-related potential (ERP) but also in a change in the ongoing EEG/MEG in form of an event-related desynchronization (ERD) or event-related synchronization (ERS). The ERP on the one side and the ERD/ERS on the other side are different responses of neuronal structures in the brain. While the former is phase-locked, the latter is not phase-locked to the event. The most important difference between both phenomena is that the ERD/ERS is highly frequency band-specific, whereby either the same or different locations on the scalp can display ERD and ERS simultaneously. Quantification of ERD/ERS in time and space is demonstrated on data from a number of movement experiments.
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paper_title: "Virtual keyboard" controlled by spontaneous EEG activity

paper_content:

A "virtual keyboard" (VK) is a letter spelling device operated for example by spontaneous electroencephalogram (EEG), whereby the EEC is modulated by mental hand and leg motor imagery. We report on three able-bodied subjects, operating the VK. The ability in the use of the VK varies between 0.85 and 0.5 letters/min in error-free writing.
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paper_title: How many people are able to control a P300-based brain–computer interface (BCI)?

paper_content:

An EEG-based brain–computer system can be used to control external devices such as computers, wheelchairs or Virtual Environments. One of the most important applications is a spelling device to aid severely disabled individuals with communication, for example people disabled by amyotrophic lateral sclerosis (ALS). P300-based BCI systems are optimal for spelling characters with high speed and accuracy, as compared to other BCI paradigms such as motor imagery. In this study, 100 subjects tested a P300based BCI system to spell a 5-character word with only 5 min of training. EEG data were acquired while the subject looked at a 36-character matrix to spell the word WATER. Two different versions of the P300 speller were used: (i) the row/column speller (RC) that flashes an entire column or row of characters and (ii) a single character speller (SC) that flashes each character individually. The subjects were free to decide which version to test. Nineteen subjects opted to test both versions. The BCI system classifier was trained on the data collected for the word WATER. During the real-time phase of the experiment, the subject spelled the word LUCAS, and was provided with the classifier selection accuracy after each of the five letters. Additionally, subjects filled out a questionnaire about age, sex, education, sleep duration, working duration, cigarette consumption, coffee consumption, and level of disturbance that the flashing characters produced. 72.8% (N = 81) of the subjects were able to spell with 100% accuracy in the RC paradigm and 55.3% (N = 38) of the subjects spelled with 100% accuracy in the SC paradigm. Less than 3% of the subjects did not spell any character correctly. People who slept less than 8 h performed significantly better than other subjects. Sex, education, working duration, and cigarette and coffee consumption were not statistically related to differences in accuracy. The disturbance of the flashing characters was rated with a median score of 1 on a scale from 1 to 5 (1, not disturbing; 5, highly disturbing). This study shows that high spelling accuracy can be achieved with the P300 BCI system using approximately 5 min of training data for a large number of non-disabled subjects, and that the RC paradigm is superior to the SC paradigm. 89% of the 81 RC subjects were able to spell with accuracy 80–100%. A similar study using a motor imagery BCI with 99 subjects showed that only 19% of the subjects were able to achieve accuracy of 80–100%. These large differences in accuracy suggest that with limited amounts of training data the P300-based BCI is superior to the motor imagery BCI. Overall, these results are very encouraging and a similar study should be conducted with subjects who have ALS to determine if their accuracy levels are similar.
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paper_title: A P300 event-related potential brain–computer interface (BCI): The effects of matrix size and inter stimulus interval on performance

paper_content:

We describe a study designed to assess properties of a P300 brain–computer interface (BCI). The BCI presents the user with a matrix containing letters and numbers. The user attends to a character to be communicated and the rows and columns of the matrix briefly intensify. Each time the attended character is intensified it serves as a rare event in an oddball sequence and it elicits a P300 response. The BCI works by detecting which character elicited a P300 response. We manipulated the size of the character matrix (either 3 � 3o r 6� 6) and the duration of the inter stimulus interval (ISI) between intensifications (either 175 or 350 ms). Online accuracy was highest for the 3 � 3 matrix 175-ms ISI condition, while bit rate was highest for the 6 � 6 matrix 175-ms ISI condition. Average accuracy in the best condition for each subject was 88%. P300 amplitude was significantly greater for the attended stimulus and for the 6 � 6 matrix. This work demonstrates that matrix size and ISI are important variables to consider when optimizing a BCI system for individual users and that a P300-BCI can be used for effective communication. # 2006 Elsevier B.V. All rights reserved.
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paper_title: A BCI-based environmental controller for the motion-disabled

paper_content:

With the development of brain-computer interface (BCI) technology, researchers are now attempting to put current BCI techniques into practical application. This paper presents an environmental controller using a BCI technique based on steady-state visual evoked potential. The system is composed of a stimulator, a digital signal processor, and a trainable infrared remote-controller. The attractive features of this system include noninvasive signal recording, little training requirement, and a high information transfer rate. Our test results have shown that this system can distinguish at least 48 targets and provide a transfer rate up to 68 b/min. The system has been applied to the control of an electric apparatus successfully.
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paper_title: A human computer interface using SSVEP-based BCI technology

paper_content:

To address the issue of system simplicity and subject applicability, a brain controlled HCI system derived from steady state visual evoked potential (SSVEP) based brain computer interface (BCI) is proposed in this paper. Aiming at an external input device for personal computer, key issues of hardware and software design for better performance and user-friendly interface are introduced systematically. With proper parameter customization for each individual, an average information transfer rate of 46bits/min was achieved in the operation of dialing a phone number. With encouraging online performance and advantages of system simplicity, the proposed HCI using SSVEP-based BCI technology is promising for a substitute of standard computer input device for both health and disabled computer users.
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paper_title: P300-based brain computer interface: Reliability and performance in healthy and paralysed participants

paper_content:

Abstract Objective This study aimed to describe the use of the P300 event-related potential as a control signal in a brain computer interface (BCI) for healthy and paralysed participants. Methods The experimental device used the P300 wave to control the movement of an object on a graphical interface. Visual stimuli, consisting of four arrows (up, right, down, left) were randomly presented in peripheral positions on the screen. Participants were instructed to recognize only the arrow indicating a specific direction for an object to move. P300 epochs, synchronized with the stimulus, were analyzed on-line via Independent Component Analysis (ICA) with subsequent feature extraction and classification by using a neural network. Results We tested the reliability and the performance of the system in real-time. The system needed a short training period to allow task completion and reached good performance. Nonetheless, severely impaired patients had lower performance than healthy participants. Conclusions The proposed system is effective for use with healthy participants, whereas further research is needed before it can be used with locked-in syndrome patients. Significance The P300-based BCI described can reliably control, in ‘real time’, the motion of a cursor on a graphical interface, and no time-consuming training is needed in order to test possible applications for motor-impaired patients.
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paper_title: BCI2000: a general-purpose brain-computer interface (BCI) system

paper_content:

Many laboratories have begun to develop brain-computer interface (BCI) systems that provide communication and control capabilities to people with severe motor disabilities. Further progress and realization of practical applications depends on systematic evaluations and comparisons of different brain signals, recording methods, processing algorithms, output formats, and operating protocols. However, the typical BCI system is designed specifically for one particular BCI method and is, therefore, not suited to the systematic studies that are essential for continued progress. In response to this problem, we have developed a documented general-purpose BCI research and development platform called BCI2000. BCI2000 can incorporate alone or in combination any brain signals, signal processing methods, output devices, and operating protocols. This report is intended to describe to investigators, biomedical engineers, and computer scientists the concepts that the BCI2000 system is based upon and gives examples of successful BCI implementations using this system. To date, we have used BCI2000 to create BCI systems for a variety of brain signals, processing methods, and applications. The data show that these systems function well in online operation and that BCI2000 satisfies the stringent real-time requirements of BCI systems. By substantially reducing labor and cost, BCI2000 facilitates the implementation of different BCI systems and other psychophysiological experiments. It is available with full documentation and free of charge for research or educational purposes and is currently being used in a variety of studies by many research groups.
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paper_title: Friend: A Communication Aid for Persons With Disabilities

paper_content:

Computers offer valuable opportunities to people with physical disabilities. For example, a computer can allow someone with severe speech and motor-impairment to engage more fully with the world. This paper describes the design of a communication aid for motor-impaired users, who literally use computers as their communication partners. Currently, a low cost interface suitable for different types of motor-impaired users is hardly available. Additionally, the target audience of existing such systems is very much limited. The present work solved these problems by its adaptation mechanism. The adaptation mechanism provides an appropriate interface from an interface bank for each user before start of an interaction. The adaptation mechanism is continued during as well as after the end of interactions to make the system personalized to individual user.
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paper_title: Users with Disabilities: Maximum Control with Minimum Effort

paper_content:

People with disabilities can benefit greatly from services provided by computers and robots. Access to remote communications and information as well as to interpersonal communication and environmental control are assisted by current ubiquitous computers, wired and wireless networks and intelligent environments. Sensory, physical or/and cognitive restrictions to interacting with computers can be avoided by means of alternative interaction devices and procedures. Nevertheless, alternative methods are usually much slower than standard communications, frequently leading users with disabilities into unbalanced or unsafe situations. Therefore, the main challenge of human-machine interaction systems that have to be used by people with disabilities is to obtain the maximum communication and control with the minimum physical and cognitive effort from the user. This lecture overviews the main techniques used to optimize the control and communication flow, resulting in higher user satisfaction and security.
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paper_title: The Tufts-MIT Prescription Guide: Assessment of Users to Predict the Suitability of Augmentative Communication Devices

paper_content:

Under contract to the National Institute of Neurological and Communicative Disorders and Stroke, we developed a system for prescribing augmentative communication devices for motor-impaired, nonvocal people. The system is novel in that it scores devices for their suitability for a client based on assessments that do not involve trial-and-error evaluation of client performance with devices. The “benchmarks” it calculates are designed to be predictive of the overall utility of a device given the client's needs, and of the communication rate the client will achieve with it once it has become completely familiar. The scoring process is performed by a program known as the Tufts-MIT Prescription Guide, which runs on IBM XT-compatible computers. Special-purpose assessment instrumentation has been developed to perform the motor-assessment tasks required by the Guide to estimate expert rate. An exhaustive questionnaire is used to get at the device features and functions that will be useful and preferable to a clien...
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paper_title: Defining brain–machine interface applications by matching interface performance with device requirements

paper_content:

Abstract Interaction with machines is mediated by human–machine interfaces (HMIs). Brain–machine interfaces (BMIs) are a particular class of HMIs and have so far been studied as a communication means for people who have little or no voluntary control of muscle activity. In this context, low-performing interfaces can be considered as prosthetic applications. On the other hand, for able-bodied users, a BMI would only be practical if conceived as an augmenting interface. In this paper, a method is introduced for pointing out effective combinations of interfaces and devices for creating real-world applications. First, devices for domotics, rehabilitation and assistive robotics, and their requirements, in terms of throughput and latency, are described. Second, HMIs are classified and their performance described, still in terms of throughput and latency. Then device requirements are matched with performance of available interfaces. Simple rehabilitation and domotics devices can be easily controlled by means of BMI technology. Prosthetic hands and wheelchairs are suitable applications but do not attain optimal interactivity. Regarding humanoid robotics, the head and the trunk can be controlled by means of BMIs, while other parts require too much throughput. Robotic arms, which have been controlled by means of cortical invasive interfaces in animal studies, could be the next frontier for non-invasive BMIs. Combining smart controllers with BMIs could improve interactivity and boost BMI applications.
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paper_title: Information transfer rate in a five-classes brain-computer interface

paper_content:

The information transfer rate, given in bits per trial, is used as an evaluation measurement in a brain-computer interface (BCI). Three subjects performed four motor-imagery (left hand, right hand, foot, and tongue) and one mental-calculation task. Classification of the EEG patterns is based on band power estimates and hidden Markov models. We propose a method that combines the EEG patterns based on separability into subsets of two, three, four, and five mental tasks. The information transfer rates of the BCI systems comprised of these subsets are reported. The achieved information transfer rates vary from 0.42 to 0.81 bits per trial and reveal that the upper limit of different mental tasks for a BCI system is three. In each subject, different combinations of three tasks resulted in the best performance.
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paper_title: Brain–computer interfaces for communication and control

paper_content:

Abstract For many years people have speculated that electroencephalographic activity or other electrophysiological measures of brain function might provide a new non-muscular channel for sending messages and commands to the external world – a brain–computer interface (BCI). Over the past 15 years, productive BCI research programs have arisen. Encouraged by new understanding of brain function, by the advent of powerful low-cost computer equipment, and by growing recognition of the needs and potentials of people with disabilities, these programs concentrate on developing new augmentative communication and control technology for those with severe neuromuscular disorders, such as amyotrophic lateral sclerosis, brainstem stroke, and spinal cord injury. The immediate goal is to provide these users, who may be completely paralyzed, or ‘locked in’, with basic communication capabilities so that they can express their wishes to caregivers or even operate word processing programs or neuroprostheses. Present-day BCIs determine the intent of the user from a variety of different electrophysiological signals. These signals include slow cortical potentials, P300 potentials, and mu or beta rhythms recorded from the scalp, and cortical neuronal activity recorded by implanted electrodes. They are translated in real-time into commands that operate a computer display or other device. Successful operation requires that the user encode commands in these signals and that the BCI derive the commands from the signals. Thus, the user and the BCI system need to adapt to each other both initially and continually so as to ensure stable performance. Current BCIs have maximum information transfer rates up to 10–25 bits/min. This limited capacity can be valuable for people whose severe disabilities prevent them from using conventional augmentative communication methods. At the same time, many possible applications of BCI technology, such as neuroprosthesis control, may require higher information transfer rates. Future progress will depend on: recognition that BCI research and development is an interdisciplinary problem, involving neurobiology, psychology, engineering, mathematics, and computer science; identification of those signals, whether evoked potentials, spontaneous rhythms, or neuronal firing rates, that users are best able to control independent of activity in conventional motor output pathways; development of training methods for helping users to gain and maintain that control; delineation of the best algorithms for translating these signals into device commands; attention to the identification and elimination of artifacts such as electromyographic and electro-oculographic activity; adoption of precise and objective procedures for evaluating BCI performance; recognition of the need for long-term as well as short-term assessment of BCI performance; identification of appropriate BCI applications and appropriate matching of applications and users; and attention to factors that affect user acceptance of augmentative technology, including ease of use, cosmesis, and provision of those communication and control capacities that are most important to the user. Development of BCI technology will also benefit from greater emphasis on peer-reviewed research publications and avoidance of the hyperbolic and often misleading media attention that tends to generate unrealistic expectations in the public and skepticism in other researchers. With adequate recognition and effective engagement of all these issues, BCI systems could eventually provide an important new communication and control option for those with motor disabilities and might also give those without disabilities a supplementary control channel or a control channel useful in special circumstances.
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paper_title: Pointing Device Usage Guidelines for People With Quadriplegia: A Simulation and Validation Study Utilizing an Integrated Pointing Device Apparatus

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This study undertakes a simulation and validation experiment to provide guidelines regarding pointing device usage for quadriplegic individuals assisted by a newly developed integrated pointing device apparatus (IPDA). The simulation experiment involving 30 normal subjects whose upper limb movement was restricted by splints. Another 15 subjects with high level cervical spinal cord injury (SCI) were recruited for the validation study. All normal subjects employed six control modes for target-acquisition and drag-and-drop tasks using an IPDA to integrate common pointing devices. A previously designed software was used to evaluate the operational efficiency (OE), expressed as "able performance" (%AP), of the subjects. The experimental results indicated that the OE of normal subjects for controlling the pointing devices were dominated first by using the unilateral hand (69-100 %AP), then by using the wrist/hand (65-73 %AP), and finally by using either bilateral body parts or the combination of limb and chin (45-53 %AP). The OE for operating an orientation-rotated mouse using the dominant wrist/hand via IPDA in both tasks was equivalent to that for operating a trackball using the dominant hand. The experimental results obtained by subjects with SCI also demonstrated similar findings, although the OEs in each control mode were lower than in normal subjects. Results of this study provide valuable guidelines for selecting and integrating common pointing devices using IPDA for quadriplegic individuals. The priority for selecting which body part should control the pointing devices was as follows: unilateral hands, unilateral wrist/hands, and either bilateral body parts or a limb and chin/head/neck in combination.
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paper_title: A Magneto-Inductive Sensor Based Wireless Tongue-Computer Interface

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We have developed a noninvasive, unobtrusive magnetic wireless tongue-computer interface, called "Tongue Drive," to provide people with severe disabilities with flexible and effective computer access and environment control. A small permanent magnet secured on the tongue by implantation, piercing, or tissue adhesives, is utilized as a tracer to track the tongue movements. The magnetic field variations inside and around the mouth due to the tongue movements are detected by a pair of three-axial linear magneto-inductive sensor modules mounted bilaterally on a headset near the user's cheeks. After being wirelessly transmitted to a portable computer, the sensor output signals are processed by a differential field cancellation algorithm to eliminate the external magnetic field interference, and translated into user control commands, which could then be used to access a desktop computer, maneuver a powered wheelchair, or control other devices in the user's environment. The system has been successfully tested on six able-bodied subjects for computer access by defining six individual commands to resemble mouse functions. Results show that the Tongue Drive system response time for 87% correctly completed commands is 0.8 s, which yields to an information transfer rate of approximately 130 b/min.
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paper_title: Application of tilt sensors in human-computer mouse interface for people with disabilities

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This study describes the motivation and the design considerations of an economical head-operated computer mouse. In addition, it focuses on the invention of a head-operated computer mouse that employs two tilt sensors placed in the headset to determine head position and to function as simple head-operated computer mouse. One tilt sensor detects the lateral head-motion to drive the left/right displacement of the mouse. The other one detects the head's vertical motion to move up and down with respect to the displacement of the mouse. A touch switch device was designed to contact gently with operator's cheek. Operator may puff his cheek to trigger the device to perform single click, double clicks, and drag commands. This system was invented to assist people with disabilities to live an independent professional life.
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paper_title: EEG-based communication: improved accuracy by response verification

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Humans can learn to control the amplitude of electroencephalographic (EEG) activity in specific frequency bands over sensorimotor cortex and use it to move a cursor to a target on a computer screen. EEG-based communication could provide a new augmentative communication channel for individuals with motor disabilities. In the present system, each dimension of cursor movement is controlled by a linear equation. While the intercept in the equation is continually updated, it does not perfectly eliminate the impact of spontaneous variations in EEG amplitude. This imperfection reduces the accuracy of cursor movement. The authors evaluated a response verification (RV) procedure in which each outcome is determined by two opposite trials (e.g., one top-target trial and one bottom-target trial). Success, or failure, on both is required for a definitive outcome. The RV procedure reduces errors due to imperfection in intercept selection. Accuracy for opposite-trial pairs exceeds that predicted from the accuracies of individual trials, and greatly exceeds that for same-trial pairs. The RV procedure should be particularly valuable when the first trial has >2 possible targets, because the second trial need only confirm or deny the outcome of the first, and it should be applicable to nonlinear as well as to linear algorithms.
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paper_title: The Camera Mouse: visual tracking of body features to provide computer access for people with severe disabilities

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The "Camera Mouse" system has been developed to provide computer access for people with severe disabilities. The system tracks the computer user's movements with a video camera and translates them into the movements of the mouse pointer on the screen. Body features such as the tip of the user's nose or finger can be tracked. The visual tracking algorithm is based on cropping an online template of the tracked feature from the current image frame and testing where this template correlates in the subsequent frame. The location of the highest correlation is interpreted as the new location of the feature in the subsequent frame. Various body features are examined for tracking robustness and user convenience. A group of 20 people without disabilities tested the Camera Mouse and quickly learned how to use it to spell out messages or play games. Twelve people with severe cerebral palsy or traumatic brain injury have tried the system, nine of whom have shown success. They interacted with their environment by spelling out messages and exploring the Internet.
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paper_title: Psychology of human-computer interaction

paper_content:

Contents: Preface. An Applied Information-Processing Psychology. Part I: Science Base. The Human Information-Processor. Part II: Text-Editing. System and User Variability. An Exercise in Task Analysis. The GOMS Model of Manuscript Editing. Extensions of the GOMS Analysis. Models of Devices for Text Selection. Part III: Engineering Models. The Keystroke-Level Model. The Unit-Task Level of Analysis. Part IV: Extensions and Generalizations. An Exploration into Circuit Design. Cognitive Skill. Applying Psychology to Design Reprise.
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paper_title: THE INFORMATION CAPACITY OF THE HUMAN MOTOR SYSTEM IN CONTROLLING THE AMPLITUDE OF MOVEMENT 1

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Information theory has recently been employed to specify more precisely than has hitherto been possible man's capacity in certain sensory, perceptual, and perceptual-motor functions (5, 10, 13, 15, 17, 18). The experiments reported in the present paper extend the theory to the human motor system. The applicability of only the basic concepts, amount of information, noise, channel capacity, and rate of information transmission, will be examined at this time. General familiarity with these concepts as formulated by recent writers (4, 11,20, 22) is assumed. Strictly speaking, we cannot study man's motor system at the behavioral level in isolation from its associated sensory mechanisms. We can only analyze the behavior of the entire receptor-neural-effector system. However, by asking 51 to make rapid and uniform responses that have been highly overlearned, and by holding all relevant stimulus conditions constant with the exception of those resulting from 5"s own movements, we can create an experimental situation in which it is reasonable to assume that performance is limited primarily by the capacity of the motor system. The motor system in the present case is defined as including the visual and proprioceptive feedback loops that permit S to monitor his own activity. The information capacity of the motor system is specified by its ability to produce consistently one class of movement from among several alternative movement classes. The greater the number of alternative classes, the greater is the information capacity of a particular type of response. Since measurable aspects of motor responses, such as their force, direction, and amplitude, are continuous variables, their information capacity is limited only by the amount of statistical variability, or noise, that is characteristic of repeated efforts to produce the same response. The information capacity of the motor Editor's Note. This article is a reprint of an original work published in 1954 in the Journal of Experimental Psychology, 47, 381391.
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paper_title: Optimizing Assisted Communication Devices for Children With Motor Impairments Using a Model of Information Rate and Channel Capacity

paper_content:

For children who depend on devices to communicate, the rate of communication is a primary determinant of success. For children with motor impairments, the rate of communication may be limited by inability to contact buttons or cells rapidly or accurately. It is, therefore, essential to know how to adjust the device interface in order to maximize each child's rate of communication. The optimal rate of communication is determined by the channel capacity, which is the maximum value of the information rate for all possible keyboard button or cell layouts for the communication device. We construct a mathematical model for the information rate based on the relationship between movement time and the number of buttons per screen, the size of the buttons, and the length of a sequence of buttons that must be pressed to communicate each word in the vocabulary. We measure the parameters of the model using a custom-programmed touchscreen interface in 10 children with disorders of arm movement due to cerebral palsy who use a DynaVox communication device. We measure the same parameters in 20 healthy control subjects. We show that the model approximates the measured information rate and that the information rate is lower in children with motor impairments compared with control subjects. The theory predicts that for each child there is a combination of button size and number that maximizes the predicted information rate and thereby achieves communication at the optimal channel capacity. Programming communication devices with each child's predicted optimal parameters improved the communication rate in five of the ten children, compared with programming by professionals. Therefore, measurement of information rate may provide an assessment of the effect of motor disorders on success in assisted communication. Optimization of the information rate may be useful for programming assisted communication devices.
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paper_title: On the rate of gain of information.

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Abstract The analytical methods of information theory are applied to the data obtained in certain choice-reaction-time experiments. Two types of experiment were performed: (a) a conventional choice-reaction experiment, with various numbers of alternatives up to ten, and with a negligible proportion of errors, and (b) a ten-choice experiment in which the subjects deliberately reduced their reaction time by allowing themselves various proportions of errors. The principal finding is that the rate of gain of information is, on the average, constant with respect to time, within the duration of one perceptual-motor act, and has a value of the order of five “bits” per second. The distribution of reaction times among the ten stimuli in the second experiment is shown to be related to the objective uncertainty as to which response will be given to each stimulus. The distribution of reaction times among the responses is also related to the same uncertainty. This is further evidence that information is intimately con...
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paper_title: Modeling the speed of text entry with a word prediction interface

paper_content:

This study analyzes user performance of text entry tasks with word prediction by applying modeling techniques developed in the field of human-computer interaction. Fourteen subjects transcribed text with and without a word prediction feature for seven test sessions. Eight subjects were able-bodied and used mouthstick typing, while six subjects bad high-level spinal cord injuries and used their usual method of keyboard access. Use of word prediction decreased text generation rate for the spinal cord injured subjects and only modestly enhanced it for the able-bodied subjects. This suggests that the cognitive cost of using word prediction had a major impact on the performance of these subjects. Performance was analyzed in more detail by deriving subjects' times for keypress and list search actions during word prediction use. All subjects had slower keypress times during word prediction use as compared to letters-only typing, and spinal cord injured subjects had much slower list search times than able-bodied subjects. These parameter values were used in a two-parameter model to simulate subjects' word entry times during word prediction use, with an average model error of 16%. These simulation results are an encouraging first step toward demonstrating the ability of analytical models to represent user performance with word prediction. >
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paper_title: Adaptive software for head-operated computer controls

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Head-operated computer controls provide an alternative means of computer access for people with disabilities who are unable to use a standard mouse. However, a person's disability may limit his or her neck movements as well as upper extremity movements. Software was developed which automatically adjusts the interface sensitivity to the needs of a particular user. This adaptive software was evaluated in two stages. First, 16 novice head-control users with spinal-cord injury or multiple sclerosis used head controls with and without the adaptive software. The adaptive software was associated with increased speed in standardized icon selection exercises (p<0.05). A small increase in accuracy was also observed. In addition, five current head-control users evaluated the software in a real-world setting. One of these five subjects perceived an improvement in comparison to his current head-control system.
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paper_title: Children with congenital spastic hemiplegia obey Fitts’ Law in a visually guided tapping task

paper_content:

Fitts' Law is commonly found to apply to motor tasks involving precise aiming movements. Children with cerebral palsy (CP) have severe difficulties in such tasks and it is unknown whether they obey Fitts' Law despite their motor difficulties. If Fitts' Law still does apply to these children, this would indicate that this law is extremely robust and that even performance of children with damaged central nervous systems can adhere to it. The integrity of motor control processes in spastic CP is usually tested in complex motor tasks, making it difficult to determine whether poor performance is due to a motor output deficit or to problems related to cognitive processes since both affect movement precision. In the present study a simple task was designed to evaluate Fitts' Law. Tapping movements were evaluated in 22 children with congenital spastic hemiplegia (CSH) and 22 typically developing children. Targets (2.5 and 5 cm in width) were placed at distances of 10 and 20 cm from each other in order to provide Indices of Difficulty (ID) of 2-4 bits. Using this Fitts' aiming task, prolonged reaction and movement time (MT) were found in the affected hand under all conditions in children with CSH as compared to controls. Like in the control group, MT in children with CSH was related to ID. The intercept 'a', corresponding to the time required to realize a tapping movement, was higher in the affected hand of the children in the CSH group. Although, the slope b (which reflects the sensitivity of the motor system to a change in difficulty of the task) and the reciprocal of slope (that represents the cognitive information processing capacity, expressed in bits/s) were similar in both groups. In conclusion, children with CSH obey Fitts' Law despite very obvious limitations in fine motor control.
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paper_title: Accuracy measures for evaluating computer pointing devices

paper_content:

In view of the difficulties in evaluating computer pointing devices across different tasks within dynamic and complex systems, new performance measures are needed. This paper proposes seven new accuracy measures to elicit (sometimes subtle) differences among devices in precision pointing tasks. The measures are target re-entry, task axis crossing, movement direction change, orthogonal direction change, movement variability, movement error, and movement offset. Unlike movement time, error rate, and throughput, which are based on a single measurement per trial, the new measures capture aspects of movement behaviour during a trial. The theoretical basis and computational techniques for the measures are described, with examples given. An evaluation with four pointing devices was conducted to validate the measures. A causal relationship to pointing device efficiency (viz. throughput) was found, as was an ability to discriminate among devices in situations where differences did not otherwise appear. Implications for pointing device research are discussed.
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paper_title: Evaluation of Head Orientation and Neck Muscle EMG Signals as Command Inputs to a Human–Computer Interface for Individuals With High Tetraplegia

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We investigated the performance of three user interfaces for restoration of cursor control in individuals with tetraplegia: head orientation, electromyography (EMG) from face and neck muscles, and a standard computer mouse (for comparison). Subjects engaged in a 2-D, center-out, Fitts' Law style task and performance was evaluated using several measures. Overall, head orientation commanded motion resembled mouse commanded cursor motion (smooth, accurate movements to all targets), although with somewhat lower performance. EMG commanded movements exhibited a higher average speed, but other performance measures were lower, particularly for diagonal targets. Compared to head orientation, EMG as a cursor command source was less accurate, was more affected by target direction and was more prone to overshoot the target. In particular, EMG commands for diagonal targets were more sequential, moving first in one direction and then the other rather than moving simultaneous in the two directions. While the relative performance of each user interface differs, each has specific advantages depending on the application.
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paper_title: Imaging of computer input ability for patient with tetraplegia

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In rehabilitation medicine, it is necessary for medical staff members to recommend the suitable computer input device for each patient with a spinal cord injury. This paper describes a measurement and evaluation system to determine the computer input ability of patients with tetraplegia. The authors will define a measurement procedure, a set of objective parameters, and a graphical representation of the parameters. They measure the position locus of the mouse cursor when a patient operates a computer using a computer input device. Using the representation, the medical staff can evaluate the patient's computer input ability and understand the characteristics of the patient's computer operation
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paper_title: Evaluation of a modified Fitts law brain–computer interface target acquisition task in able and motor disabled individuals

paper_content:

A brain–computer interface (BCI) is a communication system that takes recorded brain signals and translates them into real-time actions, in this case movement of a cursor on a computer screen. This work applied Fitts' law to the evaluation of performance on a target acquisition task during sensorimotor rhythm-based BCI training. Fitts' law, which has been used as a predictor of movement time in studies of human movement, was used here to determine the information transfer rate, which was based on target acquisition time and target difficulty. The information transfer rate was used to make comparisons between control modalities and subject groups on the same task. Data were analyzed from eight able-bodied and five motor disabled participants who wore an electrode cap that recorded and translated their electroencephalogram (EEG) signals into computer cursor movements. Direct comparisons were made between able-bodied and disabled subjects, and between EEG and joystick cursor control in able-bodied subjects. Fitts' law aptly described the relationship between movement time and index of difficulty for each task movement direction when evaluated separately and averaged together. This study showed that Fitts' law can be successfully applied to computer cursor movement controlled by neural signals.
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paper_title: Neck range of motion and use of computer head controls

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Computer head controls provide an alternative means of computer access for people with disabilities. However, a person?s ability to use head controls may be reduced if his or her disability involves neck movement limitations. In this study, 15 subjects without disabilities and 10 subjects with disabilities received neck range of motion evaluations and performed computer exercises using head controls. Regression analysis was used to determine the relationship between neck range of motion and performance on computer exercises. Reduced neck range of motion was found to be correlated with reduced functional range for moving the cursor across the screen, and reduced accuracy and speed in icon selection. Fitts' Law-type models were fit to the data, indicating higher Fitts' law slopes for subjects with disabilities compared to subjects without disabilities. Results also indicate that vertical cursor movements are faster than horizontal or diagonal movements.
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paper_title: Psychology of human-computer interaction

paper_content:

Contents: Preface. An Applied Information-Processing Psychology. Part I: Science Base. The Human Information-Processor. Part II: Text-Editing. System and User Variability. An Exercise in Task Analysis. The GOMS Model of Manuscript Editing. Extensions of the GOMS Analysis. Models of Devices for Text Selection. Part III: Engineering Models. The Keystroke-Level Model. The Unit-Task Level of Analysis. Part IV: Extensions and Generalizations. An Exploration into Circuit Design. Cognitive Skill. Applying Psychology to Design Reprise.
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paper_title: Conception and Experimentation of a Communication Device with Adaptive Scanning

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For some people with motor disabilities and speech disorders, the only way to communicate and to have some control over their environment is through the use of a controlled scanning system operated by a single switch. The main problem with these systems is that the communication process tends to be exceedingly slow, since the system must scan through the available choices one at a time until the desired message is reached. One way of raising the speed of message selection is to optimize the elementary scanning delay in real time so that it allows the user to make selections as quickly as possible without making too many errors. With this objective in mind, this article presents a method for optimizing the scanning delay, which is based on an analysis of the data recorded in “log files” while applying the EDiTH system [Digital Teleaction Environment for People with Disabilities]. This analysis makes it possible to develop a human-machine interaction model specific to the study, and then to establish an adaptive algorithm for the calculation of the scanning delay. The results obtained with imposed scenarios and then in ecological situations provides a confirmation that our algorithms are effective in dynamically adapting a scan speed. The main advantage offered by the procedure proposed is that it works on timing information alone and thus does not require any knowledge of the scanning device itself. This allows it to work with any scanning device.
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paper_title: Investigating the applicability of user models for motion-impaired users

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This paper considers the differences between users with motion-impairments and able-bodied users when they interact with computers and the implications for user models. Most interface design and usability assessment practices are based on explicit or implicit models of user behaviour. This paper studies the applicability of an existing interface design user model to motion-impaired users for the relatively straightforward task of button activation. A discussion of the empirical results is provided and the paper concludes that there are significant differences between the behaviour of motion-impaired users and the accepted modelling theory.
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paper_title: Text composition by the physically disabled: A rate prediction model for scanning input

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Abstract Keyboard ‘bypass’ techniques allow physically disabled people, otherwise unable to use conventional means of text composition, to do so. Ability to compose text is extremely important to the disabled, offering potential for non-speech communication, computer access, creative writing, etc. Consequently, these techniques have received a good deal of attention and many diverse systems have evolved. They all suffer, however, from the drawback of inherently slow input, quite apart from any disability on the part of the user. For this reason, text composition rate (or communication rate) is the major figure of merit. Since many diverse systems and approaches exist, quantitative methods of comparison are required to guide prescription and development of such aids. Only recently have attempts to produce models which predict communication rate been made. This paper extends the earlier model of Rosen and Gooenough-Trepagnier to encompass scanning-input systems. Scanning input is of considerable interest since it can be used by very severely disabled people. The model developed is applied to the comparison of two very different systems: row-column scanning and the ‘scanning Microwriter’. According to the model, row-scanning is very much faster than the scanning Microwriter when a letter-frequency arrangement of the character selections is used. The relation of the model to classical information theory, treating the disabled user as an information source, is also explored.
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paper_title: Performance Models for Automatic Evaluation of Virtual Scanning Keyboards

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Virtual scanning keyboards are commonly used augmentative communication aids by persons with severe speech and motion impairments. Designers of virtual scanning keyboards face problems in evaluating alternate designs and hence in choosing the better design among alternatives. Automatic evaluation of designs will be helpful to designers in making the appropriate design choice. In this paper, we present performance models for virtual scanning keyboards that can be used for automatic evaluation. The proposed models address the limitations present in the reported work on similar models. We compared the model predictions with results from user trials and established the validity of the proposed models.
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paper_title: Customised text entry devices for motor-impaired users.

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The standard QWERTY keyboard is the principal text entry device for word processing and computer-based communications. For many motor-impaired individuals, and in particular those without intelligible speech, the low text entry rates they can typically achieve is a major problem. For some, the QWERTY design is completely inappropriate. Alternative designs that can appreciably increase these rates would greatly enhance their ability to communicate. This paper considers and compares several approaches to the design of text entry devices for motor-impaired users. A general method for customising (i e, optimising) these designs is employed, and consideration is given to designs requiring significantly fewer input switches than the 26 or more keys required by QWERTY. Use is made of language statistics in the design procedure, and the increased availability of inexpensive, powerful computers is directly exploited.
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paper_title: EEG-based neuroprosthesis control: A step towards clinical practice

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Abstract This case study demonstrates the coupling of an electroencephalogram (EEG)-based Brain–Computer Interface (BCI) with an implanted neuroprosthesis (Freehand ® system). Because the patient was available for only 3 days, the goal was to demonstrate the possibility of a patient gaining control over the motor imagery-based Graz BCI system within a very short training period. By applying himself to an organized and coordinated training procedure, the patient was able to generate distinctive EEG-patterns by the imagination of movements of his paralyzed left hand. These patterns consisted of power decreases in specific frequency bands that could be classified by the BCI. The output signal of the BCI emulated the shoulder joystick usually used, and by consecutive imaginations the patient was able to switch between different grasp phases of the lateral grasp that the Freehand ® system provided. By performing a part of the grasp-release test, the patient was able to move a simple object from one place to another. The results presented in this work give evidence that Brain–Computer Interfaces are an option for the control of neuroprostheses in patients with high spinal cord lesions. The fact that the user learned to control the BCI in a comparatively short time indicates that this method may also be an alternative approach for clinical purposes.
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paper_title: EMG-Based Speech Recognition Using Hidden Markov Models With Global Control Variables

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It is well known that a strong relationship exists between human voices and the movement of articulatory facial muscles. In this paper, we utilize this knowledge to implement an automatic speech recognition scheme which uses solely surface electromyogram (EMG) signals. The sequence of EMG signals for each word is modelled by a hidden Markov model (HMM) framework. The main objective of the work involves building a model for state observation density when multichannel observation sequences are given. The proposed model reflects the dependencies between each of the EMG signals, which are described by introducing a global control variable. We also develop an efficient model training method, based on a maximum likelihood criterion. In a preliminary study, 60 isolated words were used as recognition variables. EMG signals were acquired from three articulatory facial muscles. The findings indicate that such a system may have the capacity to recognize speech signals with an accuracy of up to 87.07%, which is superior to the independent probabilistic model.
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paper_title: Real-time implementation of electromyogram pattern recognition as a control command of man-machine interface.

paper_content:

The purpose of this study was to develop a real-time electromyogram (EMG) discrimination system to provide control commands for man-machine interface applications. A host computer with a plug-in data acquisition and processing board containing a TMS320 C31 floating-point digital signal processor was used to attain real-time EMG classification. Two-channel EMG signals were collected by two pairs of surface electrodes located bilaterally between the sternocleidomastoid and the upper trapezius. Five motions of the neck and shoulders were discriminated for each subject. The zero-crossing rate was employed to detect the onset of muscle contraction. The cepstral coefficients, derived from autoregressive coefficients and estimated by a recursive least square algorithm, were used as the recognition features. These features were then discriminated using a modified maximum likelihood distance classifier. The total response time of this EMG discrimination system was achieved about within 0.17 s. Four able bodied and two C5/6 quadriplegic subjects took part in the experiment, and achieved 95% mean recognition rate in discrimination between the five specific motions. The response time and the reliability of recognition indicate that this system has the potential to discriminate body motions for man-machine interface applications.
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paper_title: A P300 event-related potential brain–computer interface (BCI): The effects of matrix size and inter stimulus interval on performance

paper_content:

We describe a study designed to assess properties of a P300 brain–computer interface (BCI). The BCI presents the user with a matrix containing letters and numbers. The user attends to a character to be communicated and the rows and columns of the matrix briefly intensify. Each time the attended character is intensified it serves as a rare event in an oddball sequence and it elicits a P300 response. The BCI works by detecting which character elicited a P300 response. We manipulated the size of the character matrix (either 3 � 3o r 6� 6) and the duration of the inter stimulus interval (ISI) between intensifications (either 175 or 350 ms). Online accuracy was highest for the 3 � 3 matrix 175-ms ISI condition, while bit rate was highest for the 6 � 6 matrix 175-ms ISI condition. Average accuracy in the best condition for each subject was 88%. P300 amplitude was significantly greater for the attended stimulus and for the 6 � 6 matrix. This work demonstrates that matrix size and ISI are important variables to consider when optimizing a BCI system for individual users and that a P300-BCI can be used for effective communication. # 2006 Elsevier B.V. All rights reserved.
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paper_title: Enhanced hybrid electromyogram/Eye Gaze Tracking cursor control system for hands-free computer interaction.

paper_content:

This paper outlines the development and initial testing of a new hybrid computer cursor control system based on Eye Gaze Tracking (EGT) and electromyogram (EMG) processing for hands-free control of the computer cursor. The ultimate goal of the system is to provide an efficient computer interaction mechanism for individuals with severe motor disabilities (or specialized operators whose hands are committed to other tasks, such as surgeons, pilots, etc.) The paper emphasizes the enhancements that have been made on different areas of the architecture, with respect to a previous prototype developed by our group, and demonstrates the performance improvement verified for some of the enhancements.
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paper_title: Human-machine interface for wheelchair control with EMG and its evaluation

paper_content:

The objective of this paper is to develop a powered wheelchair controller based on EMG for users with high-level spinal cord injury. EMG is very naturally measured when the user indicating a certain direction and the force information which will be used for the speed of wheelchair is easily extracted from EMG. Furthermore, the emergency situation based on EMG will be checked relatively ease. We classified the pre-defined motions such as rest case, forward movement, left movement, and right movement by fuzzy min-max neural networks (FMMNN). This classification results and evaluation results with real users shows the feasibility of EMG as an input interface for powered wheelchair.
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paper_title: Development of a hybrid hands-off human computer interface based on electromyogram signals and eye-gaze tracking

paper_content:

A hybrid hands-off human computer interface that uses infrared video eye gaze tracking (EGT) and electromyogram (EMG) signals is introduced. This system combines the advantages of both sub-systems, providing quick cursor displacement In long excursions and steady, accurate movement in small position adjustments. The hybrid system also provides a reliable clicking mechanism. The evaluation protocol used to test the system is described and the results for the hybrid, an EMG Only interface, and the standard hand-held mouse are described and compared. These results show that the hybrid system is, in an average, faster than the EMG-only system by a factor of 2 or more.
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paper_title: Session independent non-audible speech recognition using surface electromyography

paper_content:

In this paper we introduce a speech recognition system based on myoelectric signals. The system handles audible and non-audible speech. Major challenges in surface electromyography based speech recognition ensue from repositioning electrodes between recording sessions, environmental temperature changes, and skin tissue properties of the speaker. In order to reduce the impact of these factors, we investigate a variety of signal normalization and model adaptation methods. An average word accuracy of 97.3% is achieved using seven EMG channels and the same electrode positions. The performance drops to 76.2% after repositioning the electrodes if no normalization or adaptation is performed. By applying our adaptation methods we manage to restore the recognition rates to 87.1%. Furthermore, we compare audibly to non-audibly spoken speech. The results suggest that large differences exist between the corresponding muscle movements. Still, our recognition system recognizes both speech manners accurately when trained on pooled data
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paper_title: Myoelectric Signals for Multimodal Speech Recognition

paper_content:

A Coupled Hidden Markov Model (CHMM) is proposed in this paper to perform multimodal speech recognition using myoeletric signals (MES) from the muscles of vocal articulation. MES signals are immune to noise, and words that are acoustically similar manifest distinctly in MES. Hence, they would effectively complement the acoustic data in a multimodal speech recognition system. Research in Audio-Visual Speech Recognition has shown that CHMMs model the asynchrony between different data streams effectively. Hence, we propose CHMM for multimodal speech recognition using audio and MES as the two data streams. Our experiments indicate that the multimodal CHMM system significantly outperforms the audio only system at different SNRs. We have also provided a comparison between different features for MES and have found that wavelet features provide the best results.
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paper_title: A practical EMG-based human-computer interface for users with motor disabilities

paper_content:

In line with the mission of the Assistive Technology Act of 1998 (ATA), this study proposes an integrated assistive real-time system which "affirms that technology is a valuable tool that can be used to improve the lives of people with disabilities." An assistive technology device is defined by the ATA as "any item, piece of equipment, or product system, whether acquired commercially, modified, or customized, that is used to increase, maintain, or improve the functional capabilities of individuals with disabilities." The purpose of this study is to design and develop an alternate input device that can be used even by individuals with severe motor disabilities. This real-time system design utilizes electromyographic (EMG) biosignals from cranial muscles and electroencephalographic (EEG) biosignals from the cerebrum's occipital lobe, which are transformed into controls for two-dimensional (2-D) cursor movement, the left-click (Enter) command, and an ON/OFF switch for the cursor-control functions. This HCI system classifies biosignals into "mouse" functions by applying amplitude thresholds and performing power spectral density (PSD) estimations on discrete windows of data. Spectral power summations are aggregated over several frequency bands between 8 and 500 Hz and then compared to produce the correct classification. The result is an affordable DSP-based system that, when combined with an on-screen keyboard, enables the user to fully operate a computer without using any extremities.
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paper_title: Multimodal neuroelectric interface development

paper_content:

We are developing electromyographic and electroencephalographic methods, which draw control signals for human-computer interfaces from the human nervous system. We have made progress in four areas: 1) real-time pattern recognition algorithms for decoding sequences of forearm muscle activity associated with control gestures; 2) signal-processing strategies for computer interfaces using electroencephalogram (EEG) signals; 3) a flexible computation framework for neuroelectric interface research; and d) noncontact sensors, which measure electromyogram or EEG signals without resistive contact to the body.
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paper_title: Drifting and Blinking Compensation in Electro-oculography (EOG) Eye-gaze Interface

paper_content:

This paper describes an eye-gaze interface using a biological signal, electro-oculorgram (EOG). This interface enables a user to move a computer cursor on a graphical user interface using eye gaze movement alone. It will be useful as a communication aid for individuals with mobility handicaps. Although EOG is easily recordable, drifting and blinking problems must be solved to produce a reliable eye-gaze interface. Here we introduced a calibration method and a feedback control to overcome these problems.
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paper_title: Nessi: An EEG-Controlled Web Browser for Severely Paralyzed Patients

paper_content:

We have previously demonstrated that an EEG-controlled web browser based on self-regulation of slow cortical potentials (SCPs) enables severely paralyzed patients to browse the internet independently of any voluntary muscle control. However, this system had several shortcomings, among them that patients could only browse within a limited number of web pages and had to select links from an alphabetical list, causing problems if the link names were identical or if they were unknown to the user (as in graphical links). Here we describe a new EEG-controlled web browser, called Nessi, which overcomes these shortcomings. In Nessi, the open source browser, Mozilla, was extended by graphical in-place markers, whereby different brain responses correspond to different frame colors placed around selectable items, enabling the user to select any link on a web page. Besides links, other interactive elements are accessible to the user, such as e-mail and virtual keyboards, opening up a wide range of hypertext-based applications.
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paper_title: Application of facial electromyography in computer mouse access for people with disabilities.

paper_content:

Purpose. This study develops a newly facial EMG human – computer interface for people with disabilities for controllng the movement of the cursor on a computer screen.Method. We access the computer cursor according to different facial muscle activity patterns. In order to exactly detect the muscle activity threshold, this study adopts continuous wavelet transformation to estimate the single motor unit action potentials dynamically.Result. The experiment indicates that the accuracy of using the facial mouse is greater than 80%, and this result indicates the feasibility of the proposed system. Moreover, the subject can improve performance of manipulation by repeated training.Conclusion. Compared with previous works, the proposed system achieves complete cursor function and provides an inexpensive solution. Although there are still some drawbacks in the facial EMG-based human – computer interface, the facial mouse can provide an alternative among other expensive and complicated assistive technologies.
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paper_title: A BCI-based environmental controller for the motion-disabled

paper_content:

With the development of brain-computer interface (BCI) technology, researchers are now attempting to put current BCI techniques into practical application. This paper presents an environmental controller using a BCI technique based on steady-state visual evoked potential. The system is composed of a stimulator, a digital signal processor, and a trainable infrared remote-controller. The attractive features of this system include noninvasive signal recording, little training requirement, and a high information transfer rate. Our test results have shown that this system can distinguish at least 48 targets and provide a transfer rate up to 68 b/min. The system has been applied to the control of an electric apparatus successfully.
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paper_title: New classification algorithm for electromyography-based computer cursor control system

paper_content:

At present, a three-input electromyography (EMG) system has been created to provide real-time, hands-free cursor control. The system uses the real-time spectral analysis of three EMG signals to produce the following five cursor actions: i) LEFT, ii) RIGHT, iii) UP, iv) DOWN, v) LEFT-CLICK. The three EMG signals are obtained from two surface electrodes placed on the left and right temples of the head and one electrode placed in the forehead region. The present system for translating EMG activity into cursor actions does not always discriminate between up and down EMG activity efficiently. To resolve this problem it was proposed that the three-electrode system be converted into a four-electrode system, using two electrodes in the forehead of the user, instead of one. This paper compares the effectiveness of the four-electrode system to that of the three-electrode system in classifying EMG activity into cursor actions through the use of Matlab simulations. It will be shown that the new four-electrode system produces significant improvements in classification performance.
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paper_title: Talking off the top of your head: toward a mental prosthesis utilizing event-related brain potentials

paper_content:

Abstract This paper describes the development and testing of a system whereby one can communicate through a computer by using the P300 component of the event-related brain potential (ERP). Such a system may be used as a communication aid by individuals who cannot use any motor system for communication (e.g., ‘locked-in’ patients). The 26 letters of the alphabet, together with several other symbols and commands, are displayed on a computer screen which serves as the keyboard or prosthetic device. The subject focuses attention successively on the characters he wishes to communicate. The computer detects the chosen character on-line and in real time. This detection is achieved by repeatedly flashing rows and columns of the matrix. When the elements containing the chosen character are flashed, a P300 is elicited, and it is this P300 that is detected by the computer. We report an analysis of the operating characteristics of the system when used with normal volunteers, who took part in 2 experimental sessions. In the first session (the pilot study/training session) subjects attempted to spell a word and convey it to a voice synthesizer for production. In the second session (the analysis of the operating characteristics of the system) subjects were required simply to attend to individual letters of a word for a specific number of trials while data were recorded for off-line analysis. The analyses suggest that this communication channel can be operated accurately at the rate of 0.20 bits/sec. In other words, under the conditions we used, subjects can communicate 12.0 bits, or 2.3 characters, per min.
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paper_title: Multi-stream HMM for EMG-based speech recognition

paper_content:

A technique for improving the recognition accuracy of EMG-based speech recognition by applying existing speech recognition technologies is proposed. The authors have proposed an EMG-based speech recognition system that requires only mouth movements, voice need not be generated. A multi-stream HMM (hidden Markov model) and feature extraction technique are applied to EMG-based speech recognition. 3 channel facial EMG signals are collected from ten subjects when uttering 10 Japanese isolated digits. One channel corresponds to one stream. By examining various features, we found that the delta component of the static parameter leads to higher accuracy. Compared to equal stream weighting, the individual optimization of stream weights increased recognition accuracy by 4.0% which corresponds to a 12.8% reduction in error rate. This result shows that multistream HMM is effective for the classification of EMG.
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paper_title: Development of communication supporting device controlled by eye movements and voluntary eye blink

paper_content:

A communication support interface controlled by eye movements and voluntary eye blink has been developed for disabled individuals with motor paralysis who cannot speak. Horizontal and vertical electro-oculograms were measured using two surface electrodes attached above and beside the dominant eye and referring to an earlobe electrode and amplified with AC-coupling in order to reduce the unnecessary drift. Four directional cursor movements ---up, down, right, and left--- and one selected operation were realized by logically combining the two detected channel signals based on threshold settings specific to the individual. Letter input experiments were conducted on a virtual screen keyboard. The method's usability was enhanced by minimizing the number of electrodes and applying training to both the subject and the device. As a result, an accuracy of 90.1 ± 3.6% and a processing speed of 7.7 ± 1.9 letters/min. were obtained using our method.
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paper_title: EMG based voice recognition

paper_content:

Besides its clinical applications, various researchers have shown that EMG can be utilised in areas such as computer human interface and in developing intelligent prosthetic devices. The paper presents results from a preliminary study. The work describes the outcome in using an artificial neural network (ANN) to recognise and classify human speech based on EMG. The EMG signals were acquired from three articulatory facial muscles. Three subjects were selected and participated in the experiments. Preliminarily, five English vowels were used as recognition variables. The root mean square (RMS) values of the EMG signals were estimated and used as a set of features to feed the ANN. The findings indicate that such a system may have the capacity to recognise and classify speech signals with an accuracy of up to 88%.
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paper_title: Design of the human/computer interface for human with disability using myoelectric signal control

paper_content:

The purpose of this study is to develop a human-computer interface (HCI) application based on a real-time EMG discrimination system. A personal computer with a plug-in data acquisition and processing board containing a floating-point digital signal processor are used to attain real-time EMG classification. The integrated EMG is employed to detect the onset of muscle contraction. The cepstral coefficients derived from AR coefficients and estimated by a recursive least square algorithm, are used as the recognition feature. These features are then discriminated using a modified maximum likelihood distance classifier. The identified commands control the mouse cursor. It is fully compatible with a Microsoft serial mouse. This system can move the cursor in four directions, and double-click the icon in GUI operating systems.
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paper_title: A low-cost interface for control of computer functions by means of eye movements

paper_content:

Human-computer interactions (HCI) have become an important area of research and development in computer science and psychology. Appropriate use of computers could be of primary importance for communication and education of those subjects which could not move, speak, see or hear properly. The aim of our study was to develop a reliable, low-cost and easy-to-use HCI based on electrooculography signal analysis, to allow physically impaired patients to control a computer as assisted communication. Twenty healthy subjects served as volunteers: eye movements were captured by means of four electrodes and a two-channel amplifier. The output signal was then transmitted to an ''Analog to Digital'' (AD) converter, which digitized the signal of the amplifier at a rate of 500Hz, before being sent to a laptop. We designed and coded a specific software, which analyzed the input signal to give an interpretation of eye movements. By means of a single ocular movement (up, down, left and right) the subjects were then able to move a cursor over a screen keyboard, passing from one letter to another; a double eye blink was then necessary to select and write the active letter. After a brief training session, all the subjects were able to confidently control the cursor and write words using only ocular movements and blinking. For each subject we presented three series of randomized words: mean time required to enter a single character was about 8.5s, while input errors were very limited (less than 1 per 250 characters). Our results confirm those obtained in previous studies: eye-movement interface can be used to properly control computer functions and to assist communication of movement-impaired patients.
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paper_title: Neural Control of the Computer Cursor Based on Spectral Analysis of the Electromyogram

paper_content:

A classification algorithm is developed to translate facial movements into five cursor actions: i) left, ii) right, iii) up, iv) down, and v) left-click. The algorithm utilizes the unique spectral characteristics exhibited by electromyogram (EMG) signals obtained from different muscles in the face to assist in the classification process. A previous three-electrode, EMG-based system was utilized in to perform a similar translation of facial movements into cursor actions. This system also made use of spectral analysis to classify muscle activity. It was found that this system does not always discriminate between the EMG activity assigned to up and down cursor actions efficiently. To remedy this matter, a fourth electrode was added and a new classification algorithm was devised. This paper details the classification algorithm utilized with the four-electrode system. It also compares the effectiveness of the four-electrode system to that of the three-electrode system in classifying EMG activity into cursor actions. This was done through the use of Matlab simulations. It will be shown that the new four-electrode system produces significant improvements in classification performance
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paper_title: A human computer interface using SSVEP-based BCI technology

paper_content:

To address the issue of system simplicity and subject applicability, a brain controlled HCI system derived from steady state visual evoked potential (SSVEP) based brain computer interface (BCI) is proposed in this paper. Aiming at an external input device for personal computer, key issues of hardware and software design for better performance and user-friendly interface are introduced systematically. With proper parameter customization for each individual, an average information transfer rate of 46bits/min was achieved in the operation of dialing a phone number. With encouraging online performance and advantages of system simplicity, the proposed HCI using SSVEP-based BCI technology is promising for a substitute of standard computer input device for both health and disabled computer users.
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paper_title: Two-Dimensional Cursor-to-Target Control From Single Muscle Site sEMG Signals

paper_content:

In this study, human subjects achieve two-dimensional cursor-to-target control using the surface electromyogram (sEMG) from a single muscle site. The X-coordinate and the Y-coordinate of the computer cursor were simultaneously controlled by the active manipulation of power within two frequency bands of the sEMG power-spectrum. Success of the method depends on the sEMG frequency bandwidths and their midpoints. We acquired the sEMG signals at a single facial muscle site of four able-bodied subjects and trained them, by visual feedback, to control the position of the cursor. After training, all four subjects were able to simultaneously control the X and Y positions of the cursor to accurately and consistently hit three widely-separated targets on a computer screen. This technology has potential application in a wide variety of human-machine interfaces to assistive technologies.
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paper_title: Development of EOG-Based Communication System Controlled by Eight-Directional Eye Movements

paper_content:

A communication support interface controlled by eye movements and voluntary eye blink has been developed for disabled individuals with motor paralysis who cannot speak. Horizontal and vertical electro-oculograms were measured using two electrodes attached above and beside the dominant eye and referring to an earlobe electrode and amplified with AC-coupling in order to reduce the unnecessary drift. Eight directional cursor movements and one selected operation were realized by logically combining the two detected channel signals based on threshold setting specific to the individuals. As experimental results using a projected screen keyboard, processing speed was improved to 12.1 letters/min. while the accuracy was 90.4%.
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paper_title: P300-based brain computer interface: Reliability and performance in healthy and paralysed participants

paper_content:

Abstract Objective This study aimed to describe the use of the P300 event-related potential as a control signal in a brain computer interface (BCI) for healthy and paralysed participants. Methods The experimental device used the P300 wave to control the movement of an object on a graphical interface. Visual stimuli, consisting of four arrows (up, right, down, left) were randomly presented in peripheral positions on the screen. Participants were instructed to recognize only the arrow indicating a specific direction for an object to move. P300 epochs, synchronized with the stimulus, were analyzed on-line via Independent Component Analysis (ICA) with subsequent feature extraction and classification by using a neural network. Results We tested the reliability and the performance of the system in real-time. The system needed a short training period to allow task completion and reached good performance. Nonetheless, severely impaired patients had lower performance than healthy participants. Conclusions The proposed system is effective for use with healthy participants, whereas further research is needed before it can be used with locked-in syndrome patients. Significance The P300-based BCI described can reliably control, in ‘real time’, the motion of a cursor on a graphical interface, and no time-consuming training is needed in order to test possible applications for motor-impaired patients.
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paper_title: "Virtual keyboard" controlled by spontaneous EEG activity

paper_content:

A "virtual keyboard" (VK) is a letter spelling device operated for example by spontaneous electroencephalogram (EEG), whereby the EEC is modulated by mental hand and leg motor imagery. We report on three able-bodied subjects, operating the VK. The ability in the use of the VK varies between 0.85 and 0.5 letters/min in error-free writing.
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<format>
Title: Alternative communication systems for people with severe motor disabilities: a survey

Section 1: Introduction
Description 1: Summarize the evolution of assistive technology (AT) devices for people with motor disabilities, focusing on alternative communication systems based on bioelectricity (EMG, EOG, and EEG).

Section 2: Switch based control and Proportional Biosignals sensors
Description 2: Describe the classification of human-machine interface sensors into switch-based control (SBC) and proportional sensor (PRO) types, with examples of their application in communication aids.

Section 3: EMG signal
Description 3: Explain the generation of EMG signals, types of electrodes used, and the acquisition process, including the applications of electromyography in communication aid devices.

Section 4: EMG applications
Description 4: Discuss the various applications of EMG signals in communication devices, such as switch-based control, mouse emulation, and speech recognition.

Section 5: EOG signal
Description 5: Describe the characteristics, acquisition methods, and potential applications of EOG signals in assistive communication systems.

Section 6: EOG applications
Description 6: Detail the specific applications of EOG signals in communication aids, including cursor control and writing systems.

Section 7: Electroencephalography
Description 7: Provide an overview of EEG-based brain-computer interfaces (BCI) for communication, discussing both invasive and non-invasive methods, and their application in assistive technologies.

Section 8: Asynchronous BCI
Description 8: Discuss the principles, advantages, and challenges of asynchronous BCI systems that use spontaneous cortical potentials.

Section 9: Synchronous BCI
Description 9: Explain synchronous BCI systems that rely on evoked potentials like P300 and SSVEP, including their advantages and challenges.

Section 10: Considerations about synchronous and asynchronous BCIs
Description 10: Compare synchronous and asynchronous BCI systems, and discuss the trade-offs and considerations in choosing the type of interface for assistive communication devices.

Section 11: Performance evaluation
Description 11: Review the methods and metrics used to evaluate the performance of alternative communication systems.

Section 12: Measurements of performance without interaction model
Description 12: Discuss performance measurement criteria based on user experiments, and describe various criteria used in the evaluation of communication interfaces.

Section 13: Direct communication
Description 13: Explore models of user performance for text entry tasks using direct control of keyboards and touchscreens.

Section 14: Pointing Tasks
Description 14: Examine the application of Fitts' Law and other metrics for evaluating pointing devices' performance in assistive communication.

Section 15: Scanning systems
Description 15: Analyze scanning systems for communication, focusing on optimizing communication rate and evaluating user performance.

Section 16: Conclusions
Description 16: Summarize the findings and discussions of the various communication systems and their applications, highlighting the importance of individualized assessment in deploying these technologies.

</format>
