A Comparative Study of Conventional and Tripolar EEG for
  High-Performance Reach-to-Grasp BCI Systems
Ali Rabiee Sima Ghafoori Anna Cetera Walter Besio Reza Abiri
This study aims to enhance BCI applications for individuals with motor
impairments by comparing the effectiveness of tripolar EEG (tEEG) with
conventional EEG. The focus is on interpreting and decoding various grasping
movements, such as power grasp and precision grasp. The goal is to determine
which EEG technology is more effective in processing and translating grasp
related neural signals. The approach involved experimenting on ten healthy
participants who performed two distinct grasp movements: power grasp and
precision grasp, with a no movement condition serving as the baseline. Our
research presents a thorough comparison between EEG and tEEG in decoding
grasping movements. This comparison spans several key parameters, including
signal to noise ratio (SNR), spatial resolution via functional connectivity,
ERPs, and wavelet time frequency analysis. Additionally, our study involved
extracting and analyzing statistical features from the wavelet coefficients,
and both binary and multiclass classification methods were employed. Four
machine learning algorithms were used to evaluate the decoding accuracies. Our
results indicated that tEEG demonstrated superior performance over conventional
EEG in various aspects. This included a higher signal to noise ratio, enhanced
spatial resolution, and more informative data in ERPs and wavelet time
frequency analysis. The use of tEEG led to notable improvements in decoding
accuracy for differentiating movement types. Specifically, tEEG achieved around
90% accuracy in binary and 75.97% for multiclass classification. These results
are markedly better than those from standard EEG, which recorded a maximum of
77.85% and 61.27% in similar tasks, respectively. These findings highlight the
superior effectiveness of tEEG over EEG in decoding grasp types and its
competitive or superior performance in complex classifications compared with
existing research.