Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review
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paper_title: Neural network approach for non-invasive detection of hyperglycemia using electrocardiographic signals

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Hyperglycemia or high blood glucose (sugar) level is a common dangerous complication among patients with Type 1 diabetes mellitus (T1DM). Hyperglycemia can cause serious health problems if left untreated such as heart disease, stroke, vision and nerve problems. Based on the electrocardiographic (ECG) parameters, we have identified hyperglycemic and normoglycemic states in T1DM patients. In this study, a classification unit is introduced with the approach of feed forward multi-layer neural network to detect the presences of hyperglycemic/normoglycemic episodes using ECG parameters as inputs. A practical experiment using the real T1DM patients' data sets collected from Department of Health, Government of Western Australia is studied. Experimental results show that proposed ECG parameters contributed significantly to the good performance of hyperglycemia detections in term of sensitivity, specificity and geometric mean (70.59%, 65.38%, and 67.94%, respectively). From these results, it is proved that hyperglycemic events in T1DM can be detected non-invasively and effectively by using ECG signals and ANN approach.
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paper_title: Noninvasive Glucose Monitoring: Increasing Accuracy by Combination of Multi-Technology and Multi-Sensors

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BACKGROUND ::: The main concern in noninvasive (NI) glucose monitoring methods is to achieve high accuracy results despite the fact that no direct blood or interstitial fluid glucose measurement is performed. An alternative approach to increase the accuracy of NI glucose measurement was previously suggested through a combination of three NI methods: ultrasonic, electromagnetic, and thermal. This paper provides further explanation about the nature of the implemented technologies, and multi-sensors are presented, as well as a detailed elaboration on the novel algorithm for data analysis. ::: ::: ::: METHODS ::: Clinical trials were performed on two different days. During the first day, calibration and six subsequent measurements were performed. During the second day, a "full day" session of about 10 hours took place. During the trial, type 1 and 2 diabetes patients were calibrated and evaluated with GlucoTrack glucose monitor against HemoCue (Glucose 201+). ::: ::: ::: RESULTS ::: A total of 91 subjects were tested during the trial period. Clarke error grid (CEG) analysis shows 96% of the readings (on both days 1 and 2) fall in the clinically accepted A and B zones, of which 60% are within zone A. The absolute relative differences (ARDs) yield mean and median values of 22.4% and 15.9%, respectively. The CEG for day 2 of the trial shows 96% of the points in zones A and B, with 57% of the values in zone A. Mean and median ARD values for the readings on day 2 are 23.4% and 16.5%, respectively. The intervals between day 1 (calibration and measurements) and day 2 (measurements only) were 1-22 days, with a median of 6 days. ::: ::: ::: CONCLUSIONS ::: The presented methodology shows that increased accuracy was indeed achieved by combining multi-technology and multi-sensors. The approach of integration contributes to increasing the signal-to-noise ratio (glucose to other contributors). A combination of several technologies allows compensation of a possible aberration in one modality by the others, while multi-sensor implementation enables corrections for interference contributions. Furthermore, clinical trials indicate the ability of using the device for a wide range of demography, showing clearly that the calibration is valid for long term.
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paper_title: Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation

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The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1kHz-100MHz, 1 and 2GHz) as well as optical characterisation. In this paper we describe the results of using an MGMS in a miniaturised housing with fully integrated sensors and battery. Six patients with Type I Diabetes Mellitus (age 44+/-16y; BMI 24.1+/-1.3kg/m(2), duration of diabetes 27+/-12y; HbA1c 7.3+/-1.0%) wore a single Multisensor at the upper arm position and performed a total of 45 in-clinic study days with 7 study days per patient on average (min. 5 and max. 10). Glucose changes were induced either orally or by i.v. glucose administration and the blood glucose was measured routinely. Several prospective data evaluation routines were applied to evaluate the data. The results are shown using one of the restrictive data evaluation routines, where measurements from the first 22 study days were used to train a linear regression model. The global model was then prospectively applied to the data of the remaining 23 study days to allow for an external validation of glucose prediction. The model application yielded a Mean Absolute Relative Difference of 40.8%, a Mean Absolute Difference of 51.9mgdL(-1), and a correlation of 0.84 on average per study day. The Clarke error grid analyses showed 89.0% in A+B, 4.5% in C, 4.6% in D and 1.9% in the E region. Prospective application of a global, purely statistical model, demonstrates that glucose variations can be tracked non invasively by the MGMS in most cases under these conditions.
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paper_title: Hypoglycemia detection based on cardiac repolarization features

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Hypoglycemia is known to affect repolarization characteristics of the heart. These changes are shown from ECG by prolonged QT-time and T-wave flattening. In this study we constructed a classifier based on these ECG parameters. By using the classifier we tried to detect hypoglycemic events from measurements of 22 test subjects. Hypoglycemic state was achieved using glucose clamp technique. Used test protocol consisted of three stages: normoglycemic period, transition period (blood glucose concentration decreasing) and hypoglycemic period. Subjects were divided into three groups: 9 healthy controls (Healthy), 6 otherwise healthy type 1 diabetics (T1DM) and 7 type 1 diabetics with disease complications (T1DMc). Detection of hypoglycemic event could be made passably from 15/22 measurements. In addition, we found that detection process is easier for healthy and T1DM groups than T1DMc group diabetics because in T1DMc group subjects' have lower autonomic response to hypoglycemic events. Also we noticed that changes in ECG occurs few minutes after blood glucose is decreased below 3.5 mmol/1.
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paper_title: Incorporating an Exercise Detection, Grading, and Hormone Dosing Algorithm Into the Artificial Pancreas Using Accelerometry and Heart Rate

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In this article, we present several important contributions necessary for enabling an artificial endocrine pancreas (AP) system to better respond to exercise events. First, we show how exercise can be automatically detected using body-worn accelerometer and heart rate sensors. During a 22 hour overnight inpatient study, 13 subjects with type 1 diabetes wearing a Zephyr accelerometer and heart rate monitor underwent 45 minutes of mild aerobic treadmill exercise while controlling their glucose levels using sensor-augmented pump therapy. We used the accelerometer and heart rate as inputs into a validated regression model. Using this model, we were able to detect the exercise event with a sensitivity of 97.2% and a specificity of 99.5%. Second, from this same study, we show how patients' glucose declined during the exercise event and we present results from in silico modeling that demonstrate how including an exercise model in the glucoregulatory model improves the estimation of the drop in glucose during exercise. Last, we present an exercise dosing adjustment algorithm and describe parameter tuning and performance using an in silico glucoregulatory model during an exercise event.
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paper_title: Effects of hyperglycemia on variability of RR, QT and corrected QT intervals in Type 1 diabetic patients

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In this study, we evaluated the effects of hyperglycemia on the variability of RR (HRV), QT interval variability (QTV) and corrected QT interval variability (QTcV) during hyperglycemic and non-hyperglycemic conditions in six Type 1 diabetic patients at nights. The aim of this study was to investigate the association of high blood glucose levels with autonomic modulation of heart rate and variation in ventricular repolarization. Blood glucose level (BGL) threshold for defining hyperglycemia state was set at 8.33 mmol/l. Variability of RR, QT and corrected QT intervals during hyperglycemic and non-hyperglycemic were quantified using time and frequency domain measures. Hypomon® device was used to monitor ECG signals and acquire RR and QT intervals in Type 1 diabetic patients overnight. The results indicated that time and frequency domain HRV variables were significantly decreased under hyperglycemic condition and inversely correlated with BGL. QTV parameters also reduced when BGL increased and time domain measures of QTV were inversely associated with BGL. Variability in QTc interval was much less than in the QT interval and demonstrated a lower SDNN and LF power. We concluded that certain components of HRV, time-domain measures of QTV and QTc but not QTcV are strongly correlated to high blood glucose levels and can be good markers to identify hyperglycemic events in T1DM.
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paper_title: Disruption of circadian blood pressure, heart rate and the impact on glycemic control in type 1 diabetes.

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Patients with type 1 diabetes (DM-1) have an increased mortality and morbidity risk compared to non-diabetic subjects. Even not recognized clinically at the early period of disease; patients with DM-1 show subtle neurological and cardiovascular abnormalities which is partly responsible for the increased mortality. One of these abnormalities is the disruption of circadian rhythms. Various factors such as autonomic dysfunction, sleep disturbance, smoking, cardiac and kidney function, atherosclerosis, arterial stiffness are suggested to cause these disturbances. Additionally these abnormalities have also implications regarding target organ damage such as microalbuminuria, retinopathy, and structural changes in glomeruli. Surprisingly, there are scarce data regarding the effect of tight blood glucose control and insulin on circadian rhythms in patients with DM-1. By the light of aforementioned data this review will try to summarize causes and consequences of disruption of circadian rhythms and the impact on glycemic control on these issues in patients with DM-1.
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paper_title: Hypoglycaemia and QT interval prolongation in type 1 diabetes – bridging the gap between clamp studies and spontaneous episodes

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Abstract Aims We propose a study design with controlled hypoglycaemia induced by subcutaneous injection of insulin and matched control episodes to bridge the gap between clamp studies and studies of spontaneous hypoglycaemia. The observed prolongation of the heart rate corrected QT interval (QTc) during hypoglycaemia varies greatly between studies. Methods We studied ten adults with type 1 diabetes (age 41±15years) without cardiovascular disease or neuropathy. Single-blinded hypoglycaemia was induced by a subcutaneous insulin bolus followed by a control episode on two occasions separated by 4weeks. QT intervals were measured using the semi-automatic tangent approach, and QTc was derived by Bazett's (QTcB) and Fridericia's (QTcF) formulas. Results QTcB increased from baseline to hypoglycaemia (403±20 vs. 433±39ms, p Conclusions Hypoglycaemia as experienced after a subcutaneous injection of insulin may cause QTc prolongation in type 1 diabetes. However, the magnitude of prolongation is less than typically reported during glucose clamp studies, possible because of the study design with focus on minimizing unwanted study effects.
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paper_title: Daily Energy Expenditure, Cardiorespiratory Fitness and Glycaemic Control in People with Type 1 Diabetes

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OBJECTIVE ::: Encouraging daily physical activity improves cardiorespiratory fitness and many cardiovascular risk factors. However, increasing physical activity often creates a challenge for people with type 1 diabetes, because of difficulties maintaining euglycemia in the face of altered food intake and adjustments to insulin doses. Our aim was to examine the triangular relationship between glucose control measured by continuous glucose monitoring system (CGMS), objective measures of total daily energy expenditure (TEE) recorded by a multi-sensory monitoring device, and cardiorespiratory fitness (CRF), in free-living subjects with type 1 diabetes. ::: ::: ::: RESEARCH DESIGN AND METHODS ::: Twenty-three individuals (12 women) with type 1 diabetes who were free from micro- and macrovascular complications were recruited. TEE and glucose control were monitored simultaneously for up to 12 days, using a multi-sensory device and CGMS respectively. CRF was recorded as V02 max from a maximal treadmill test with the Bruce protocol. ::: ::: ::: RESULTS ::: Subjects (mean±SD) were aged 37±11 years, with BMI = 26.5±5.1 kg.m⁻², HbA1c = 7.7±1.3% (61±14 mmol/mol) and V02 max (ml.min⁻¹.kg⁻¹) = 39.9±8.4 (range 22.4-58.6). TEE (36.3±5.5 kcal.kg⁻¹.day⁻¹) was strongly associated with CRF(39.9±8.4 ml.min⁻¹.kg⁻¹) independently of sex (r = 0.63, p<0.01). However, neither TEE (r = -0.20, p = 0.36) nor CRF (r = -0.20, p = 0.39; adjusted for sex), were significantly associated with mean glycaemia measured by CGMS. ::: ::: ::: CONCLUSION ::: Higher levels of energy expenditure (due to a more active lifestyle) are associated with increased cardiorespiratory fitness, but not necessarily better glycaemic control. Since increased levels of energy expenditure and good glycaemic control are both needed to protect against diabetes-related complications our data suggest they need to be achieved independently.
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paper_title: Noninvasive Blood Glucose Monitoring With Optical Coherence Tomography: A pilot study in human subjects

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OBJECTIVE —To study the feasibility of noninvasive blood glucose monitoring using optical coherence tomography (OCT) technique in healthy volunteers. RESEARCH DESIGN AND METHODS —An OCT system with the wavelength of 1,300 nm was used in 15 healthy subjects in 18 clinical experiments. Standard oral glucose tolerance tests were performed to induce changes in blood glucose concentration. Blood samples were taken from the right arm vein every 5 or 15 min. OCT images were taken every 10–20 s from the left forearm over a total period of 3 h. The slope of the signals was calculated at the depth of 200–600 μm from the skin surface. RESULTS —A total of 426 blood samples and 8,437 OCT images and signals were collected and analyzed in these experiments. There was a good correlation between changes in the slope of noninvasively measured OCT signals and blood glucose concentrations throughout the duration of the experiments. The slope of OCT signals changed significantly (up to 2.8% per 10 mg/dl) with variation of plasma glucose values. The good correlation obtained between the OCT signal slope and blood glucose concentration is due to the coherent detection of backscattered photons, which allows measurements of OCT signal from a specific tissue layer without unwanted signal from other tissue layers. CONCLUSIONS —This pilot study demonstrated the capability of the OCT technique to monitor blood glucose concentration noninvasively in human subjects. Further studies with a larger number of subjects including diabetic subjects are planned to validate these preliminary results.
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paper_title: Glycaemic control in type 1 diabetes during real time continuous glucose monitoring compared with self monitoring of blood glucose: meta-analysis of randomised controlled trials using individual patient data

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Objective To determine the clinical effectiveness of real time continuous glucose monitoring compared with self monitoring of blood glucose in type 1 diabetes. Design Meta-analysis of randomised controlled trials. Data sources Cochrane database for randomised controlled trials, Ovid Medline, Embase, Google Scholar, lists of papers supplied by manufacturers of continuous glucose monitors, and cited literature in retrieved articles. Studies reviewed Randomised controlled trials of two or more months’ duration in men and non-pregnant women with type 1 diabetes that compared real time continuous glucose monitoring with self monitoring of blood glucose and where insulin delivery was the same in both arms. Analysis Two step meta-analysis of individual patient data with the primary outcome of final glycated haemoglobin (HbA 1c ) percentage and area under the curve of hypoglycaemia (glucose concentration 1c and hypoglycaemia. Results Six trials were identified, consisting of 449 patients randomised to continuous glucose monitoring and 443 to self monitoring of blood glucose. The overall mean difference in HbA 1c for continuous glucose monitoring versus self monitoring of blood glucose was −0.30% (95% confidence interval −0.43% to −0.17%) (−3.0, −4.3 to −1.7 mmol/mol). A best fit regression model of determinants of final HbA 1c showed that for every one day increase of sensor usage per week the effect of continuous glucose monitoring versus self monitoring of blood glucose increased by 0.150% (95% credibility interval −0.194% to −0.106%) (1.5, −1.9 to −1.1 mmol/mol) and every 1% (10 mmol/mol) increase in baseline HbA 1c increased the effect by 0.126% (−0.257% to 0.0007%) (1.3, −2.6 to 0.0 mmol/mol). The model estimates that, for example, a patient using the sensor continuously would experience a reduction in HbA 1c of about 0.9% (9 mmol/mol) when the baseline HbA 1c is 10% (86 mmol/mol). The overall reduction in area under the curve of hypoglycaemia was −0.28 (−0.46 to −0.09), corresponding to a reduction in median exposure to hypoglycaemia of 23% for continuous glucose monitoring compared with self monitoring of blood glucose. In a best fit regression model, baseline area under the curve of hypoglycaemia was only weakly related to the effect of continuous glucose monitoring compared with self monitoring of blood glucose on hypoglycaemia outcome, and sensor usage was unrelated to hypoglycaemia at outcome. Conclusions Continuous glucose monitoring was associated with a significant reduction in HbA 1c percentage, which was greatest in those with the highest HbA 1c at baseline and who most frequently used the sensors. Exposure to hypoglycaemia was also reduced during continuous glucose monitoring. The most cost effective or appropriate use of continuous glucose monitoring is likely to be when targeted at people with type 1 diabetes who have continued poor control during intensified insulin therapy and who frequently use continuous glucose monitoring.
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paper_title: Early Detection of Physical Activity for People With Type 1 Diabetes Mellitus

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BACKGROUND ::: Early detection of exercise in individuals with type 1 diabetes mellitus (T1DM) may allow changes in therapy to prevent hypoglycemia. Currently there is limited experience with automated methods that detect the onset and end of exercise in this population. We sought to develop a novel method to quickly and reliably detect the onset and end of exercise in these individuals before significant changes in blood glucose (BG) occur. ::: ::: ::: METHODS ::: Sixteen adults with T1DM were studied as outpatients using a diary, accelerometer, heart rate monitor, and continuous glucose monitor for 2 days. These data were used to develop a principal component analysis based exercise detection method. Subjects also performed 60 and 30 minute exercise sessions at 30% and 50% predicted heart rate reserve (HRR), respectively. The detection method was applied to the exercise sessions to determine how quickly the detection of start and end of exercise occurred relative to change in BG. ::: ::: ::: RESULTS ::: Mild 30% HRR and moderate 50% HRR exercise onset was identified in 6 ± 3 and 5 ± 2 (mean ± SD) minutes, while completion was detected in 3 ± 8 and 6 ± 5 minutes, respectively. BG change from start of exercise to detection time was 1 ± 6 and -1 ± 3 mg/dL, and, from the end of exercise to detection time was 6 ± 4 and -17 ± 13 mg/dL, respectively, for the 2 exercise sessions. False positive and negative ratios were 4 ± 2% and 21 ± 22%. ::: ::: ::: CONCLUSIONS ::: The novel method for exercise detection identified the onset and end of exercise in approximately 5 minutes, with an average BG change of only -6 mg/dL.
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paper_title: Use of the noninvasive GlucoWatch Biographer during exercise of varying intensity.

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The GlucoWatch Biographer (Cygnus, Inc., Redwood City, CA), a novel, noninvasive method for tracking glucose, makes frequent, automatic glucose measurements. Therefore, it potentially can provide a convenient method of tracking glycemia, particularly with exercise as an added variable in diabetes management. The purpose of the investigation was (1) to measure the effectiveness of this device, and (2) to determine the validity of its readings, during rest and exercise both indoors and outdoors. Four subjects with type 1 diabetes and five controls without diabetes participated in rest, mild [40% of heart rate reserve (HRR) for 45 min], moderate (60% of HRR for 30 min), and heavy exercise (80% of HRR for 15 min) both indoors and outdoors. Subjects monitored blood glucose levels (forearm alternate site testing), and readings were taken by the GlucoWatch during and following testing conditions. Significantly more GlucoWatch readings were obtained during rest (55.6% outdoors, 66.7% indoors) than during moderate (11.1%) or heavy (0%; P < 0.01) exercise. A similar number was obtained during mild outdoor exercise (46.6%), but not indoors (29.2%). Sweating rates corresponded to a reduced effectiveness during indoor exercise only (P < 0.01), where sweating was heavier despite higher outdoor temperatures. A weak association between GlucoWatch and matched glucometer readings (r = 0.81; P < 0.01) was found. The effectiveness of the GlucoWatch Biographer during any moderate to heavy exercise was extremely poor, as was the validity of its readings compared with forearm alternate site testing. Thus, anyone wishing to engage in daily exercise would be best advised to abstain from wearing the GlucoWatch except during rest or mild exercise.
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paper_title: Continuous Glucose Monitoring: The Future of Diabetes Management

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In Brief ::: ::: Continuous glucose monitoring (CGM) technology has the potential to revolutionize diabetes care in the near future because of the real-time feedback it provides about therapeutic interventions and variations in lifestyle or dietary intake. In short, CGM has made the attainment of near-normal blood glucose concentrations an achievable goal for most patients with diabetes. Several challenges remain to be addressed, however, including the high cost of the devices, limitations in approved clinical uses, and insurance coverage for the technology. This article reviews the CGM technology currently available in the United States, its approved uses, and its limitations.
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paper_title: The artificial pancreas: current status and future prospects in the management of diabetes

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Recent advances in insulins, insulin pumps, continuous glucose-monitoring systems, and control algorithms have resulted in an acceleration of progress in the development of artificial pancreas devices. This review discusses progress in the development of external systems that are based on subcutaneous drug delivery and subcutaneous continuous glucose monitoring. There are two major system-level approaches to achieving closed-loop control of blood glucose in diabetic individuals. The unihormonal approach uses insulin to reduce blood glucose and relies on complex safety mitigation algorithms to reduce the risk of hypoglycemia. The bihormonal approach uses both insulin to lower blood glucose and glucagon to raise blood glucose, and also relies on complex algorithms to provide for safety of the user. There are several major strategies for the design of control algorithms and supervision control for application to the artificial pancreas: proportional-integral-derivative, model predictive control, fuzzy logic, and safety supervision designs. Advances in artificial pancreas research in the first decade of this century were based on the ongoing computer revolution and miniaturization of electronic technology. The advent of modern smartphones has created the ability to utilize smartphone technology as the engineering centerpiece of an artificial pancreas. With these advances, an artificial or bionic pancreas is within reach.
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paper_title: Effect of intermittent high-intensity compared with continuous moderate exercise on glucose production and utilization in individuals with type 1 diabetes

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Previously, the decline in glycemia in individuals with type 1 diabetes has been shown to be less with intermittent high-intensity exercise (IHE) compared with continuous moderate-intensity exercise (MOD) despite the performance of a greater amount of total work. The purpose of the present study was to determine whether this lesser decline in glycemia can be attributed to a greater increment in endogenous glucose production (Ra) or attenuated glucose utilization (Rd). Nine individuals with type 1 diabetes were tested on two separate occasions, during which either a 30-min MOD or IHE protocol was performed under conditions of a euglycemic clamp in combination with the infusion of [6,6-2H]glucose. MOD consisted of continuous cycling at 40% Vo2 peak, whereas IHE involved a combination of continuous exercise at 40% Vo2 peak interspersed with additional 4-s maximal sprint efforts performed every 2 min to simulate the activity patterns of intermittent sports. During IHE, glucose Ra increased earlier and to a greater extent compared with MOD. Similarly, glucose Rd increased sooner during IHE, but the increase by the end of exercise was comparable with that elicited by MOD. During early recovery from IHE, Rd rapidly declined, whereas it remained elevated after MOD, a finding consistent with a lower glucose infusion rate during early recovery from IHE compared with MOD ( P < 0.05). The results suggest that the lesser decline in glycemia with IHE may be attributed to a greater increment in Ra during exercise and attenuated Rd during exercise and early recovery.
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paper_title: Continuous glucose monitoring systems for type 1 diabetes mellitus

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Background ::: Self-monitoring of blood glucose is essential to optimise glycaemic control in type 1 diabetes mellitus. Continuous glucose monitoring (CGM) systems measure interstitial fluid glucose levels to provide semi-continuous information about glucose levels, which identifies fluctuations that would not have been identified with conventional self-monitoring. Two types of CGM systems can be defined: retrospective systems and real-time systems. Real-time systems continuously provide the actual glucose concentration on a display. Currently, the use of CGM is not common practice and its reimbursement status is a point of debate in many countries. ::: ::: Objectives ::: To assess the effects of CGM systems compared to conventional self-monitoring of blood glucose (SMBG) in patients with diabetes mellitus type 1. ::: ::: Search methods ::: We searched The Cochrane Library, MEDLINE, EMBASE and CINAHL for the identification of studies. Last search date was June 8, 2011. ::: ::: Selection criteria ::: Randomised controlled trials (RCTs) comparing retrospective or real-time CGM with conventional self-monitoring of blood glucose levels or with another type of CGM system in patients with type 1 diabetes mellitus. Primary outcomes were glycaemic control, e.g. level of glycosylated haemoglobin A1c (HbA1c) and health-related quality of life. Secondary outcomes were adverse events and complications, CGM derived glycaemic control, death and costs. ::: ::: Data collection and analysis ::: Two authors independently selected the studies, assessed the risk of bias and performed data-extraction. Although there was clinical and methodological heterogeneity between studies an exploratory meta-analysis was performed on those outcomes the authors felt could be pooled without losing clinical merit. ::: ::: Main results ::: The search identified 1366 references. Twenty-two RCTs meeting the inclusion criteria of this review were identified. The results of the meta-analyses (across all age groups) indicate benefit of CGM for patients starting on CGM sensor augmented insulin pump therapy compared to patients using multiple daily injections of insulin (MDI) and standard monitoring blood glucose (SMBG). After six months there was a significant larger decline in HbA1c level for real-time CGM users starting insulin pump therapy compared to patients using MDI and SMBG (mean difference (MD) in change in HbA1c level -0.7%, 95% confidence interval (CI) -0.8% to -0.5%, 2 RCTs, 562 patients, I2=84%). The risk of hypoglycaemia was increased for CGM users, but CIs were wide and included unity (4/43 versus 1/35; RR 3.26, 95% CI 0.38 to 27.82 and 21/247 versus 17/248; RR 1.24, 95% CI 0.67 to 2.29). One study reported the occurrence of ketoacidosis from baseline to six months; there was however only one event. Both RCTs were in patients with poorly controlled diabetes. ::: ::: For patients starting with CGM only, the average decline in HbA1c level six months after baseline was also statistically significantly larger for CGM users compared to SMBG users, but much smaller than for patients starting using an insulin pump and CGM at the same time (MD change in HbA1c level -0.2%, 95% CI -0.4% to -0.1%, 6 RCTs, 963 patients, I2=55%). On average, there was no significant difference in risk of severe hypoglycaemia or ketoacidosis between CGM and SMBG users. The confidence interval however, was wide and included a decreased as well as an increased risk for CGM users compared to the control group (severe hypoglycaemia: 36/411 versus 33/407; RR 1.02, 95% CI 0.65 to 1.62, 4 RCTs, I2=0% and ketoacidosis: 8/411 versus 8/407; RR 0.94, 95% CI 0.36 to 2.40, 4 RCTs, I2=0%). ::: ::: Health-related quality of life was reported in five of the 22 studies. In none of these studies a significant difference between CGM and SMBG was found. Diabetes complications, death and costs were not measured. ::: ::: There were no studies in pregnant women with diabetes type 1 and in patients with hypoglycaemia unawareness. ::: ::: Authors' conclusions ::: There is limited evidence for the effectiveness of real-time continuous glucose monitoring (CGM) use in children, adults and patients with poorly controlled diabetes. The largest improvements in glycaemic control were seen for sensor-augmented insulin pump therapy in patients with poorly controlled diabetes who had not used an insulin pump before. The risk of severe hypoglycaemia or ketoacidosis was not significantly increased for CGM users, but as these events occurred infrequent these results have to be interpreted cautiously.There are indications that higher compliance of wearing the CGM device improves glycosylated haemoglobin A1c level (HbA1c) to a larger extent.
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paper_title: Invasiveness as a Barrier to Self-Monitoring of Blood Glucose in Diabetes

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Background: This study investigated the degree to which the invasive characteristic of glucose monitoring is a barrier to self-monitoring of blood glucose (SMBG). Methods: A paper-and-pencil Measure of Invasiveness as a reason for Skipping SMBG (MISS) was created and administered to 339 people with diabetes. The correlations between MISS scores and actual SMBG frequency, percent adherence to SMBG recommendations, SMBG anxiety, SMBG burden, and knowledge of the importance of glycemic control for avoiding diabetes complications were each explored. Results: On a scale of 0–28, the average MISS score was M = 4.3 (SD = 5.4, range 0–28). Fully 63% (nearly two-thirds) of respondents reported skipping SMBG because of the invasiveness of the procedure. MISS scores were negatively related to percent adherence to healthcare provider SMBG recommendations as measured by memory function of automated meters (Spearman's r= –0.47, P < 0.01). MISS scores were also negatively related to absolute SMBG frequency regardless of...
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paper_title: Non-invasive methods of glucose measurement: current status and future perspectives.

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Diabetes mellitus (DM) is a very common disease which, if a good glycemic control is not achieved, can lead to serious chronic complications such as cardiovascular disease, retinopathy, nephropathy and neuropathy. Selfmonitoring of blood glucose is a fundamental tool for the proper adjustment of the treatment of diabetes and, at present, it is based mainly on capillary blood obtained by finger-prick (the classical glucometers). Since this method is painful and the strips are expensive, investigators have been attracted by the idea of using a non-invasive device for determining blood glucose which would permit more frequent testing and a tighter control of diabetes. The non-invasive measurement of blood glucose is based on the ability of the glucose molecule to interact with various chemical or physical methods. Nevetheless, in spite of some encouraging results and the efforts made over the past 30-40 years, there is no device available at present for use in clinical practice. A possible explanation might be the combination between the specific features of each method and the specific characteristics of diabetic patients, which make them respond differently to physical and chemical methods when compared to their healthy counterparts. In this paper we will give an overview of the noninvasive devices tested so far and their implications for the clinical management of the diabetic patient.
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paper_title: Hypoglycaemia in diabetes mellitus: epidemiology and clinical implications

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Hypoglycaemia is a frequent adverse effect of some therapies for diabetes mellitus, and can have serious consequences. This Review describes the epidemiology of hypoglycaemia in adults with diabetes mellitus, principally in those treated with insulin. The consequences of hypoglycaemia are discussed, with particular focus on the cardiovascular and neurological morbidities that can occur.
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paper_title: Non-invasive glucose monitoring: assessment of technologies and devices according to quantitative criteria.

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Aim of this review was to describe the main technologies for non-invasive glucose monitoring and the corresponding most relevant devices. The review tries to overcome the limitations of previous reviews on this topic, such as the lack of objective criteria for inclusion or exclusion of technologies or devices, and the poor organization of the information, which often does not allow easy comparison between technologies and devices. In this review, the information is concise and organized into specific categories, and hence it becomes easy to compare advantages and disadvantages of the different technologies and devices. For technologies, the categories of information considered are the technology name, the underlying physical principle, the technology limitations and the measurement sites on the human body. For devices, the categories of information are the device name, its approval condition (FDA Approval and/or CE Mark), the technology on which it is based, a device general description, the tests performed on the device, the corresponding results, safety information, aspects affecting usability, current status of the device and the manufacturer, an Internet reference for the device. A total of 14 technologies and 16 devices are included. Conclusions of the review were that, despite some interesting and promising technologies and devices, a satisfactory solution to the non-invasive glucose monitoring problem still requires further efforts.
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paper_title: Electrocardiographic Signals and Swarm-Based Support Vector Machine for Hypoglycemia Detection

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Cardiac arrhythmia relating to hypoglycemia is suggested as a cause of death in diabetic patients. This article introduces electrocardiographic (ECG) parameters for artificially induced hypoglycemia detection. In addition, a hybrid technique of swarm-based support vector machine (SVM) is introduced for hypoglycemia detection using the ECG parameters as inputs. In this technique, a particle swarm optimization (PSO) is proposed to optimize the SVM to detect hypoglycemia. In an experiment using medical data of patients with Type 1 diabetes, the introduced ECG parameters show significant contributions to the performance of the hypoglycemia detection and the proposed detection technique performs well in terms of sensitivity and specificity.
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paper_title: Noninvasive Glucose Monitoring: A Novel Approach

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Background: The main concern in noninvasive (NI) glucose measurement is achieving high accuracy readings, although no blood (or other fluid) is involved in the process. Using methods based on different physical properties of a measured object can ensure the independence of each of the readings and therefore improve the validity of the end result. By using a combination of (three) independent technologies—ultrasonic, electromagnetic, and thermal— GlucoTrack™ presents a unique approach for a real-time, truly NI blood glucose spot measurement. Methods: Clinical trials were performed in two stages. Stage 1 was an initial method validation and performance verification of the device. In this stage, 50 type 1 and 2 diabetic patients, as well as healthy subjects, were evaluated with GlucoTrack against Ascensia Elite ® (Bayer). In the second stage, 85 additional diabetic subjects were evaluated in half and full daytime sessions using a GlucoTrack comparison with HemoCue ® (Glucose 201+). Results: A total of 135 subjects were tested during the trial period, producing 793 data pairs. Using Clarke error grid analysis, 92% of the readings fell in the clinically acceptable zones A and B, with 50% in the A zone. Mean and median relative absolute differences were 29.9 and 19.9%, respectively. Conclusions: Integrating several modalities for NI assessment of glucose level enables more accurate readings, while a possible aberration in one modality is bypassed by the others. The present generation of GlucoTrack gives promising results; however, further improvement of the accuracy of the device is needed.
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paper_title: Detecting Vital Signs with Wearable Wireless Sensors

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The emergence of wireless technologies and advancements in on-body sensor design can enable change in the conventional health-care system, replacing it with wearable health-care systems, centred on the individual. Wearable monitoring systems can provide continuous physiological data, as well as better information regarding the general health of individuals. Thus, such vital-sign monitoring systems will reduce health-care costs by disease prevention and enhance the quality of life with disease management. In this paper, recent progress in non-invasive monitoring technologies for chronic disease management is reviewed. In particular, devices and techniques for monitoring blood pressure, blood glucose levels, cardiac activity and respiratory activity are discussed; in addition, on-body propagation issues for multiple sensors are presented.
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paper_title: The Effect of Walking on Postprandial Glycemic Excursion in Patients With Type 1 Diabetes and Healthy People

paper_content:

OBJECTIVE Physical activity (PA), even at low intensity, promotes health and improves hyperglycemia. However, the effect of low-intensity PA captured with accelerometery on glucose variability in healthy individuals and type 1diabetes has not been examined. Quantifying the effects of PA on glycemic variability would improve artificial endocrine pancreas (AEP) algorithms. RESEARCH DESIGN AND METHODS We studied 12 healthy control subjects (five males, 37.7 ± 13.7 years of age) and 12 patients with type 1 diabetes (five males, 37.4 ± 14.2 years of age) for 88 h. Participants performed PA approximating a threefold increase over their basal metabolic rate. PA was captured using a PA-monitoring system, and interstitial fluid glucose concentrations were captured with continuous glucose monitors. In random order, one meal per day was followed by inactivity, and the other meals were followed by walking. Glucose and PA data for a total of 216 meals were analyzed from 30 min prior to meal ingestion to 270 min postmeal. RESULTS In healthy subjects, the incremental glucose area under the curve was 4.5 mmol/L/270 min for meals followed by walking, whereas it was 9.6 mmol/L/270 min ( P = 0.022) for meals followed by inactivity. The corresponding glucose excursions for those with type 1 diabetes were 7.5 mmol/L/270 min and 18.4 mmol/L/270 min, respectively ( P CONCLUSIONS Walking significantly impacts postprandial glucose excursions in healthy populations and in those with type 1 diabetes. AEP algorithms incorporating PA may enhance tight glycemic control end points.
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paper_title: Recent advances in noninvasive glucose monitoring

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The race for the next generation of painless and reliable glucose monitoring for diabetes mellitus is on. As technology advances, both diagnostic techniques and equipment improve. This review describes the main technologies currently being explored for noninvasive glucose monitoring. The principle of each technology is mentioned; its advantages and limitations are then discussed. The general description and the corresponding results for each device are illustrated, as well as the current status of the device and the manufacturer; internet references for the devices are listed where appropriate. Ten technologies and eleven potential devices are included in this review. Near infrared spectroscopy has become a promising technology, among others, for blood glucose monitoring. Although some reviews have been published already, the rapid development of technologies and information makes constant updating mandatory. While advances have been made, the reliability and the calibration of noninvasive instruments could still be improved, and more studies carried out under different physiological conditions of metabolism, bodily fluid circulation, and blood components are needed.
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paper_title: Dynamic estimation of cardiac repolarization characteristics during hypoglycemia in healthy and diabetic subjects.

paper_content:

Hypoglycemia is known to affect the repolarization characteristics of the heart, but the mechanisms behind these changes are not completely understood. We analyzed repolarization characteristics continuously from 22 subjects during normoglycemic period, transition period (blood glucose concentration decreasing) and hypoglycemic period from nine healthy controls (Healthy), six otherwise healthy type 1 diabetics (T1DM) and seven type 1 diabetics with disease complications (T1DMc). An advanced principal component regression (PCR)-based method was used for estimating ECG parameters beat-by-beat, and thus, continuous comparison between the repolarization characteristics and blood glucose values was made. We observed that hypoglycemia related ECG changes in the T1DMc group were smaller than changes in the Healthy and T1DM groups. We also noticed that when glucose concentration remained at a low level, the heart rate corrected QT interval prolonged progressively. Finally, a few minutes time lag was observed between the start of hypoglycemia and cardiac repolarization changes. One explanation for these observations could be that hypoglycemia related hormonal changes have a significant role behind the repolarization changes. This could explain at least the observed time lag (hormonal changes are slow) and the lower repolarization changes in the T1DMc group (hormonal secretion lowered in long duration diabetics).
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paper_title: QT interval prolongation during spontaneous episodes of hypoglycaemia in type 1 diabetes: the impact of heart rate correction

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AIMS/HYPOTHESIS ::: Prolongation of the heart rate corrected QT interval (QTc) is seen during episodes of hypoglycaemia in type 1 diabetes. We studied the relationship between spontaneous hypoglycaemia and the QT interval and hypothesised that the choice of heart rate correction affects the observed change in QTc. ::: ::: ::: METHODS ::: Twenty-one participants with type 1 diabetes (aged 58 +/- 10 years with duration of diabetes 34 +/- 12 years) had continuous glucose and ECG monitoring for 72 h. QT and RR intervals were measured during hypoglycaemia (blood glucose or continuous glucose measurements <or=3.5 mmol/l) and compared with euglycaemia (5-12 mmol/l). QT intervals were measured using the semi-automated tangent method from signal-averaged ECG and corrected using Bazett's formula, Fridericia's formula, the nomogram method and a linear subject-specific method. ::: ::: ::: RESULTS ::: Hypoglycaemia was present in 14 participants. With Bazett's formula, QTc changed significantly from euglycaemia to hypoglycaemia (422 +/- 30 vs 432 +/- 33 ms; p = 0.02). Heart rate, QT intervals and QTc corrected with formulas other than Bazett's were not associated with a significant change (p = 0.07-0.29). During hypoglycaemia, significantly lower values of QTc compared with the subject-specific method were seen for Fridericia's formula (p = 0.02) and the nomogram method (p = 0.04). ::: ::: ::: CONCLUSIONS/INTERPRETATION ::: Spontaneous hypoglycaemia was associated with a modest increase in QTc. Bazett's formula resulted in overcorrection of QTc while both Fridericia's formula and the nomogram method undercorrected the QTc compared with the subject-specific method during hypoglycaemia. The results may indicate that the use of a fixed heart rate correction formula can lead to misleading results in investigations of spontaneous hypoglycaemia.
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paper_title: Identification of Hypoglycemia and Hyperglycemia in Type 1 Diabetic patients using ECG parameters

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Hypoglycemia and Hyperglycemia are both serious diseases related to diabetes mellitus. Among Type 1 Diabetic patients, there are who experience both hypoglycemic and hyperglycemic events. The aim of this study was to identify of hypoglycemia and hyperglycemia based on ECG changes in this population. An ECG Acquisition and Analysis System based on LabVIEW software has been developed for collecting ECG signals and extracting features with abnormal changes. ECG parameters included Heart rate (HR), corrected QT interval (QTeC), PR interval, corrected RT interval (RTC) and corrected TpTe interval (TpTe(C)). Blood glucose levels were used to classify glycemic states in subjects as hypoglycemic state (≤ 60 mml/l, Hypo), as normoglycemic state (80 to 110 mmol/l, Normo), and as hyperglycemic state 150 mml/l, Hyper). The results indicated that hypoglycemic and hyperglycemic states produce significant inverse changes on those ECG parameters.
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paper_title: In Vitro Evaluation of Fluorescence Glucose Biosensor Response

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Rapid, accurate, and minimally-invasive glucose biosensors based on Forster Resonance Energy Transfer (FRET) for glucose measurement have the potential to enhance diabetes control. However, a standard set of in vitro approaches for evaluating optical glucose biosensor response under controlled conditions would facilitate technological innovation and clinical translation. Towards this end, we have identified key characteristics and response test methods, fabricated FRET-based glucose biosensors, and characterized biosensor performance using these test methods. The biosensors were based on competitive binding between dextran and glucose to concanavalin A and incorporated long-wavelength fluorescence dye pairs. Testing characteristics included spectral response, linearity, sensitivity, limit of detection, kinetic response, reversibility, stability, precision, and accuracy. The biosensor demonstrated a fluorescence change of 45% in the presence of 400 mg/dL glucose, a mean absolute relative difference of less than 11%, a limit of detection of 25 mg/dL, a response time of 15 min, and a decay in fluorescence intensity of 72% over 30 days. The battery of tests presented here for objective, quantitative in vitro evaluation of FRET glucose biosensors performance have the potential to form the basis of future consensus standards. By implementing these test methods for a long-visible-wavelength biosensor, we were able to demonstrate strengths and weaknesses with a new level of thoroughness and rigor.
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paper_title: Continuous glucose monitoring in type 1 diabetes

paper_content:

Continuous glucose monitors (CGM), devices that can measure interstitial glucose in “real time,” have become widely available particularly for use in patients with diabetes, and their accuracy and ease of use have greatly improved over the last decade. A number of large and well-controlled clinical trials have firmly established their usefulness in improving metabolic control (as measured by HbA1C) and decreasing time spent in hypoglycemia in adults; however, data have been less robust proving benefit in children and adolescents. Benefits are clearly linked to near-continuous wear. Insulin dosing algorithms based on CGM glucose trends have proven useful in dissecting the large volume of data generated daily by these devices, although these are imperfect tools, particularly in children. The technology is likely to be most useful when integrated with insulin pump delivery systems (sensor augmented). In this review, we concentrate on the analysis of published results of the largest trials in adults and children, including the very young, with diabetes.
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paper_title: The Effect of Walking on Postprandial Glycemic Excursion in Patients With Type 1 Diabetes and Healthy People

paper_content:

OBJECTIVE Physical activity (PA), even at low intensity, promotes health and improves hyperglycemia. However, the effect of low-intensity PA captured with accelerometery on glucose variability in healthy individuals and type 1diabetes has not been examined. Quantifying the effects of PA on glycemic variability would improve artificial endocrine pancreas (AEP) algorithms. RESEARCH DESIGN AND METHODS We studied 12 healthy control subjects (five males, 37.7 ± 13.7 years of age) and 12 patients with type 1 diabetes (five males, 37.4 ± 14.2 years of age) for 88 h. Participants performed PA approximating a threefold increase over their basal metabolic rate. PA was captured using a PA-monitoring system, and interstitial fluid glucose concentrations were captured with continuous glucose monitors. In random order, one meal per day was followed by inactivity, and the other meals were followed by walking. Glucose and PA data for a total of 216 meals were analyzed from 30 min prior to meal ingestion to 270 min postmeal. RESULTS In healthy subjects, the incremental glucose area under the curve was 4.5 mmol/L/270 min for meals followed by walking, whereas it was 9.6 mmol/L/270 min ( P = 0.022) for meals followed by inactivity. The corresponding glucose excursions for those with type 1 diabetes were 7.5 mmol/L/270 min and 18.4 mmol/L/270 min, respectively ( P CONCLUSIONS Walking significantly impacts postprandial glucose excursions in healthy populations and in those with type 1 diabetes. AEP algorithms incorporating PA may enhance tight glycemic control end points.
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paper_title: Physical activity measured by physical activity monitoring system correlates with glucose trends reconstructed from continuous glucose monitoring.

paper_content:

Abstract Background: In type 1 diabetes mellitus (T1DM), physical activity (PA) lowers the risk of cardiovascular complications but hinders the achievement of optimal glycemic control, transiently boosting insulin action and increasing hypoglycemia risk. Quantitative investigation of relationships between PA-related signals and glucose dynamics, tracked using, for example, continuous glucose monitoring (CGM) sensors, have been barely explored. Subjects and Methods: In the clinic, 20 control and 19 T1DM subjects were studied for 4 consecutive days. They underwent low-intensity PA sessions daily. PA was tracked by the PA monitoring system (PAMS), a system comprising accelerometers and inclinometers. Variations on glucose dynamics were tracked estimating first- and second-order time derivatives of glucose concentration from CGM via Bayesian smoothing. Short-time effects of PA on glucose dynamics were quantified through the partial correlation function in the interval (0, 60 min) after starting PA. Results: C...
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paper_title: Free-living inferential modeling of blood glucose level using only noninvasive inputs

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The goal of this work is to present a causation modeling methodology with the ability to accurately infer blood glucose levels using a large set of highly correlated noninvasive input variables over an extended period of time. These models can provide insight to improve glucose monitoring, and glucose regulation through advanced model-based control technologies. The efficacy of this approach is demonstrated using real data from a type 2 diabetic (T2D) subject collected under free-living conditions over a period of 25 consecutive days. The model was identified and tested using eleven variables that included three food variables as well as several activity and stress variables. The model was trained using 20 days of data and validated using 5 days of data. This gave a fitted correlation coefficient of 0.70 and an average absolute error (AAE) (i.e., the average of the absolute values for the measured glucose concentration minus modeled glucose concentration) of 13.3 mg/dL for the validation data. This AAE result was significantly better than the subject’s personal glucose meter AAE of 15.3 mg/dL for replicated measurements. Published by Elsevier Ltd.
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paper_title: Validity of the SenseWear Armband to assess energy expenditure in graded walking.

paper_content:

BACKGROUND ::: Accurate assessments of physical activity and energy expenditure (EE) are needed to advance research on positive and negative graded walking. ::: ::: ::: PURPOSE ::: To evaluate the validity of 2 SenseWear Armband monitors (Pro3 and the recently released Mini) during graded walking. ::: ::: ::: METHODS ::: Twenty healthy adults wore both monitors during randomized walking activities on a motorized treadmill at 7 grades (0%, ±5%, ±15%, and ±25%). Estimates of total EE from the monitors were computed using different algorithms and compared with values derived from indirect calorimetry methodology using a 2-way mixed model ANOVA (Device × Condition), correlation analyses and Bland-Altman plots. ::: ::: ::: RESULTS ::: There was no significant difference in EE between the 2 armbands in any of the conditions examined. Significant main effects for device and condition, as well as a consistent bias, were observed during positive and negative graded walking with a greater over- and under-estimation at higher slope. ::: ::: ::: CONCLUSIONS ::: Both the armbands produced similar EE values and seem to be not accurate in estimation of EE during activities involving uphill and downhill walking. Additional work is needed to understand factors contributing to this discrepancy and to improve the ability of these monitors to accurately measure EE during graded walking.
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paper_title: Validation of Physical Activity Monitors in Individuals with Diabetes: Energy Expenditure Estimation by the Multisensor SenseWear Armband Pro3 and the Step Counter Omron HJ-720 Against Indirect Calorimetry During Walking

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Abstract Background: The purpose of this study is to test the agreement between energy expenditure estimate of the SenseWear® Armband Pro3 (SWA) (BodyMedia, Pittsburgh, PA) and the Omron HJ-720 (Omron Healthcare, Kyoto, Japan) step counter with indirect calorimetry (IC) as a gold standard in older individuals with type 1 and type 2 diabetes mellitus while walking on a treadmill. Subjects and Methods: In total, six men (60.3±3.1 years old) and 13 women (51.1±11.0 years old) with type 1 or type 2 diabetes mellitus were included in the study. Each subject performed three 15-min walking sessions with different combinations of speed and incline (3 km/h, 0%; 4 km/h, 0%; 5 km/h, 5%) on a treadmill. Energy expenditure (EE) was simultaneously measured by the SWA, Omron, and IC. Mean over-/underestimation and Pearson's correlation coefficients were used for statistical evaluation of the agreement between tested methods and IC. Results: At the speed of 3 km/h with 0% incline, mean overestimation of +81.19±23.81% was...
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paper_title: Accuracy of a Novel Noninvasive Multisensor Technology to Estimate Glucose in Diabetic Subjects During Dynamic Conditions

paper_content:

The purpose of this study was to determine whether an approach of multisensor technology with integrated data analysis in an armband system (SenseWear® Pro Armband, SWA) can provide estimates of plasma glucose concentration in diabetes. In all, 41 subjects with diabetes participated. On day 1 subjects underwent an oral glucose tolerance test (OGTT) and on day 2 a 60-minute treadmill test (TT). SWA plasma glucose estimates were compared against reference peripheral venous glucose concentrations. A continuous glucose monitoring device (CGM) was also placed on each subject to serve as a reference for clinical comparison. Pearson coefficient, Clarke error grid (CEG), and mean absolute relative difference (MARD) analyses were used to compare the performance of plasma glucose estimation. There were significant correlations between plasma glucose concentrations estimated by the SWA and the reference plasma glucose concentration during the OGTT (r = .65, P < .05) and the TT (r = .91, P < .05). CEG analysis revealed that during the OGTT, 93% of plasma glucose concentration readings were in the clinically acceptable zone A+B for the SWA and 95% for the CGM. During the TT, the SWA had 96% of readings in zone A+B, compared to 97% for the CGM. During OGTTs, MARDs for the SWA and CGM were 26% and 18%, respectively. During TTs, MARDs were 16% and 12%, respectively. Plasma glucose concentration estimation by the SWA's noninvasive multisensor approach appears to be feasible and its performance in estimating glucose approaches that of a CGM. The success of this pilot study suggests that multisensor technology holds promising potential for the development of a wearable, noninvasive, painless glucose monitor.
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paper_title: Combining Information of Autonomic Modulation and CGM Measurements Enables Prediction and Improves Detection of Spontaneous Hypoglycemic Events

paper_content:

Background:We have previously tested, in a laboratory setting, a novel algorithm that enables prediction of hypoglycemia. The algorithm integrates information of autonomic modulation, based on heart rate variability (HRV), and data based on a continuous glucose monitoring (CGM) device. Now, we investigate whether the algorithm is suitable for prediction of hypoglycemia and for improvement of hypoglycemic detection during normal daily activities.Methods:Twenty-one adults (13 men) with T1D prone to hypoglycemia were recruited and monitored with CGM and a Holter device while they performed normal daily activities. We used our developed algorithm (a pattern classification method) to predict spontaneous hypoglycemia based on CGM and HRV. We compared 3 different models; (i) a model containing raw data from the CGM device; (ii) a CGM* model containing data derived from the CGM device signal; and (iii) a CGM+HRV model-combining model (ii) with HRV data.Results:A total of 12 hypoglycemic events (glucose levels < 3...
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paper_title: Physical Activity into the Meal Glucose—Insulin Model of Type 1 Diabetes: In Silico Studies

paper_content:

INTRODUCTION ::: A simulation model of a glucose-insulin system accounting for physical activity is needed to reliably simulate normal life conditions, thus accelerating the development of an artificial pancreas. In fact, exercise causes a transient increase of insulin action and may lead to hypoglycemia. However, physical activity is difficult to model. In the past, it was described indirectly as a rise in insulin. Recently, a new parsimonious model of exercise effect on glucose homeostasis has been proposed that links the change in insulin action and glucose effectiveness to heart rate (HR). The aim of this study was to plug this exercise model into our recently proposed large-scale simulation model of glucose metabolism in type 1 diabetes to better describe normal life conditions. ::: ::: ::: METHODS ::: The exercise model describes changes in glucose-insulin dynamics in two phases: a rapid on-and-off change in insulin-independent glucose clearance and a rapid-on/slow-off change in insulin sensitivity. Three candidate models of glucose effectiveness and insulin sensitivity as a function of HR have been considered, both during exercise and recovery after exercise. By incorporating these three models into the type 1 diabetes model, we simulated different levels (from mild to moderate) and duration of exercise (15 and 30 minutes), both in steady-state (e.g., during euglycemic-hyperinsulinemic clamp) and in nonsteady state (e.g., after a meal) conditions. ::: ::: ::: RESULTS ::: One candidate exercise model was selected as the most reliable. ::: ::: ::: CONCLUSIONS ::: A type 1 diabetes model also describing physical activity is proposed. The model represents a step forward to accurately describe glucose homeostasis in normal life conditions; however, further studies are needed to validate it against data.
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paper_title: The Impact of Accelerometer Use in Exercise-Associated Hypoglycemia Prevention in Type 1 Diabetes

paper_content:

Exercise-associated hypoglycemia is a common adverse event in people with type 1 diabetes. Previous in silico testing by our group demonstrated superior exercise-associated hypoglycemia mitigation when a predictive low glucose suspend (PLGS) algorithm was augmented to incorporate activity data. The current study investigates the effectiveness of an accelerometer-augmented PLGS algorithm in an outpatient exercise protocol. Subjects with type 1 diabetes on insulin pump therapy participated in two structured soccer sessions, one utilizing the algorithm and the other using the subject's regular basal insulin rate. Each subject wore their own insulin pump and a Dexcom G4™ Platinum continuous glucose monitor (CGM); subjects on-algorithm also wore a Zephyr BioHarness™ 3 accelerometer. The algorithm utilized a Kalman filter with a 30-minute prediction horizon. Activity and CGM readings were manually entered into a spreadsheet and at five-minute intervals, the algorithm indicated whether the basal insulin infusion should be on or suspended; any changes were then implemented by study staff. The rate of hypoglycemia during and after exercise (until the following morning) was compared between groups. Eighteen subjects (mean age 13.4 ± 3.7 years) participated in two separate sessions 7-22 days apart. The difference in meter blood glucose levels between groups at each rest period did not achieve statistical significance at any time point. Hypoglycemia during the session was recorded in three on-algorithm subjects, compared to six off-algorithm subjects. In the postexercise monitoring period, hypoglycemia occurred in two subjects who were on-algorithm during the session and four subjects who were off-algorithm. The accelerometer-augmented algorithm failed to prevent exercise-associated hypoglycemia compared to subjects on their usual basal rates. A larger sample size may have achieved statistical significance. Further research involving an automated system, a larger sample size, and an algorithm design that favors longer periods of pump suspension is necessary.
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paper_title: Adding Heart Rate Signal to a Control-to-Range Artificial Pancreas System Improves the Protection Against Hypoglycemia During Exercise in Type 1 Diabetes

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BACKGROUND ::: We present a clinical trial establishing the feasibility of a control-to-range (CTR) closed-loop system informed by heart rate (HR) and assess the effect of HR information added to CTR on the risk for hypoglycemia during and after exercise. ::: ::: ::: SUBJECTS AND METHODS ::: Twelve subjects with type 1 diabetes (five men, seven women; weight, 68.9 ± 3.1 kg; age, 38 ± 3.3 years; glycated hemoglobin, 6.9 ± 0.2%) participated in a randomized crossover clinical trial comparing CTR versus CTR+HR in two 26-h admissions, each including 30 min of mild exercise. The CTR algorithm was implemented in the DiAs portable artificial pancreas platform based on an Android(®) (Google, Mountainview, CA) smartphone. We assessed blood glucose (BG) decline during exercise, the Low BG Index (LBGI) (a measure of hypoglycemic risk), number of hypoglycemic episodes (BG <70 mg/dL) and overall glucose control (percentage time within the target range 70 mg/dL ≤ BG ≤ 180 mg/dL). ::: ::: ::: RESULTS ::: Using HR to inform the CTR algorithm reduced significantly the BG decline during exercise (P=0.022), indicated marginally lower LBGI (P=0.3) and fewer hypoglycemic events during exercise (none vs. two events; P=0.16), and resulted in overall higher percentage time within the target range (81% vs. 75%; P=0.2). LBGI and average BG remained unchanged overall, during recovery, and overnight. ::: ::: ::: CONCLUSIONS ::: HR-informed closed-loop control can be implemented in a portable artificial pancreas. Although closed loop has been shown to reduce hypoglycemia, adding HR signal may further limit the risk for hypoglycemia during and immediately after exercise. The most prominent effect of adding HR information is reduced BG decline during exercise, without deterioration of overall glycemic control.
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paper_title: Accuracy of a Novel Noninvasive Multisensor Technology to Estimate Glucose in Diabetic Subjects During Dynamic Conditions

paper_content:

The purpose of this study was to determine whether an approach of multisensor technology with integrated data analysis in an armband system (SenseWear® Pro Armband, SWA) can provide estimates of plasma glucose concentration in diabetes. In all, 41 subjects with diabetes participated. On day 1 subjects underwent an oral glucose tolerance test (OGTT) and on day 2 a 60-minute treadmill test (TT). SWA plasma glucose estimates were compared against reference peripheral venous glucose concentrations. A continuous glucose monitoring device (CGM) was also placed on each subject to serve as a reference for clinical comparison. Pearson coefficient, Clarke error grid (CEG), and mean absolute relative difference (MARD) analyses were used to compare the performance of plasma glucose estimation. There were significant correlations between plasma glucose concentrations estimated by the SWA and the reference plasma glucose concentration during the OGTT (r = .65, P < .05) and the TT (r = .91, P < .05). CEG analysis revealed that during the OGTT, 93% of plasma glucose concentration readings were in the clinically acceptable zone A+B for the SWA and 95% for the CGM. During the TT, the SWA had 96% of readings in zone A+B, compared to 97% for the CGM. During OGTTs, MARDs for the SWA and CGM were 26% and 18%, respectively. During TTs, MARDs were 16% and 12%, respectively. Plasma glucose concentration estimation by the SWA's noninvasive multisensor approach appears to be feasible and its performance in estimating glucose approaches that of a CGM. The success of this pilot study suggests that multisensor technology holds promising potential for the development of a wearable, noninvasive, painless glucose monitor.
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paper_title: A Novel Algorithm for Prediction and Detection of Hypoglycemia Based on Continuous Glucose Monitoring and Heart Rate Variability in Patients With Type 1 Diabetes

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Hypoglycemia is a common and serious side effect of insulin therapy in patients with diabetes. Early detection and prediction of hypoglycemia may improve treatment and avoidance of serious complications. Continuous glucose monitoring (CGM) has previously been used for detection of hypoglycemia, but with a modest accuracy. Therefore, our aim was to investigate whether a novel algorithm that adds information of the complex dynamic/pattern of heart rate variability (HRV) could improve the accuracy of hypoglycemia as detected by a CGM device. Data from 10 patients with type 1 diabetes studied during insulin-induced hypoglycemia were obtained. Blood glucose samples were used as reference. HRV patterns and CGM data were combined in a mathematical prediction algorithm. Detection of hypoglycemic periods, performed by the algorithm, was treated as a pattern recognition problem and features/patterns derived from HRV and CGM prior to each blood glucose sample were used to decide if that particular point in time was below the hypoglycemic threshold of 3.9 mmol/L. A total of 903 samples were analyzed by the novel algorithm, which yielded a sensitivity of 79% and a specificity of 99%. The algorithm was able to detect 16/16 hypoglycemic events with no false positives and had a lead time of 22 minutes as compared to the CGM device. Detection accuracy and lead time were significantly improved by the novel algorithm compared to that of CGM alone.
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paper_title: The Impact of Accelerometer and Heart Rate Data on Hypoglycemia Mitigation in Type 1 Diabetes

paper_content:

Aerobic exercise can lower blood glucose levels and alter insulin sensitivity both during and several hours after exercise, creating challenges for a closed-loop artificial pancreas. Predictive low glucose suspend (PLGS) algorithms are a first step toward an artificial pancreas, but few of these have been successfully applied to exercise. This study incorporates physical activity measurements from a combined accelerometer/heart rate monitor (HRM) to improve the performance of an existing PLGS algorithm at mitigating exercise-associated hypoglycemia in participants with type 1 diabetes. In all, 22 subjects with type 1 diabetes on insulin pump therapy were provided a combined accelerometer/HRM and (if not already using one) a continuous glucose monitor (CGM), then instructed to go about their everyday lives while wearing the devices. After the monitoring period, each subject's insulin pump, CGM, and accelerometer/HRM were downloaded and the data were used to augment an existing PLGS algorithm to incorporate activity. Using a computer simulator, the accelerometer-augmented algorithm was compared to the HRM-augmented algorithm to determine which was most effective at mitigating hypoglycemia. Mean length of monitoring was 4.9 days. Across all subjects, 11 061 CGM readings were recorded during the monitoring period. In the simulator analysis, the PLGS algorithm reduced hypoglycemia by 62%, compared to 71% and 74% reductions for the HRM-augmented and accelerometer-augmented algorithms, respectively; combined accelerometer and HRM augmentation provided a 76% reduction. In a simulated setting, the accelerometer-augmented pump suspension algorithm decreases the incidence of exercise-related hypoglycemia by a meaningful amount compared to the PLGS algorithm alone. Results also failed to justify the additional user burden of a HRM.
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paper_title: Multivariable adaptive closed-loop control of an artificial pancreas without meal and activity announcement.

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BACKGROUND ::: Accurate closed-loop control is essential for developing artificial pancreas (AP) systems that adjust insulin infusion rates from insulin pumps. Glucose concentration information from continuous glucose monitoring (CGM) systems is the most important information for the control system. Additional physiological measurements can provide valuable information that can enhance the accuracy of the control system. Proportional-integral-derivative control and model predictive control have been popular in AP development. Their implementations to date rely on meal announcements (e.g., bolus insulin dose based on insulin:carbohydrate ratios) by the user. Adaptive control techniques provide a powerful alternative that do not necessitate any meal or activity announcements. ::: ::: ::: MATERIALS AND METHODS ::: Adaptive control systems based on the generalized predictive control framework are developed by extending the recursive modeling techniques. Physiological signals such as energy expenditure and galvanic skin response are used along with glucose measurements to generate a multiple-input-single-output model for predicting future glucose concentrations used by the controller. Insulin-on-board (IOB) is also estimated and used in control decisions. The controllers were tested with clinical studies that include seven cases with three different patients with type 1 diabetes for 32 or 60 h without any meal or activity announcements. ::: ::: ::: RESULTS ::: The adaptive control system kept glucose concentration in the normal preprandial and postprandial range (70-180 mg/dL) without any meal or activity announcements during the test period. After IOB estimation was added to the control system, mild hypoglycemic episodes were observed only in one of the four experiments. This was reflected in a plasma glucose value of 56 mg/dL (YSI 2300 STAT; Yellow Springs Instrument, Yellow Springs, OH) and a CGM value of 63 mg/dL). ::: ::: ::: CONCLUSIONS ::: Regulation of blood glucose concentration with an AP using adaptive control techniques was successful in clinical studies, even without any meal and physical activity announcement.
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paper_title: The Effect of Walking on Postprandial Glycemic Excursion in Patients With Type 1 Diabetes and Healthy People

paper_content:

OBJECTIVE Physical activity (PA), even at low intensity, promotes health and improves hyperglycemia. However, the effect of low-intensity PA captured with accelerometery on glucose variability in healthy individuals and type 1diabetes has not been examined. Quantifying the effects of PA on glycemic variability would improve artificial endocrine pancreas (AEP) algorithms. RESEARCH DESIGN AND METHODS We studied 12 healthy control subjects (five males, 37.7 ± 13.7 years of age) and 12 patients with type 1 diabetes (five males, 37.4 ± 14.2 years of age) for 88 h. Participants performed PA approximating a threefold increase over their basal metabolic rate. PA was captured using a PA-monitoring system, and interstitial fluid glucose concentrations were captured with continuous glucose monitors. In random order, one meal per day was followed by inactivity, and the other meals were followed by walking. Glucose and PA data for a total of 216 meals were analyzed from 30 min prior to meal ingestion to 270 min postmeal. RESULTS In healthy subjects, the incremental glucose area under the curve was 4.5 mmol/L/270 min for meals followed by walking, whereas it was 9.6 mmol/L/270 min ( P = 0.022) for meals followed by inactivity. The corresponding glucose excursions for those with type 1 diabetes were 7.5 mmol/L/270 min and 18.4 mmol/L/270 min, respectively ( P CONCLUSIONS Walking significantly impacts postprandial glucose excursions in healthy populations and in those with type 1 diabetes. AEP algorithms incorporating PA may enhance tight glycemic control end points.
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paper_title: Physical activity measured by physical activity monitoring system correlates with glucose trends reconstructed from continuous glucose monitoring.

paper_content:

Abstract Background: In type 1 diabetes mellitus (T1DM), physical activity (PA) lowers the risk of cardiovascular complications but hinders the achievement of optimal glycemic control, transiently boosting insulin action and increasing hypoglycemia risk. Quantitative investigation of relationships between PA-related signals and glucose dynamics, tracked using, for example, continuous glucose monitoring (CGM) sensors, have been barely explored. Subjects and Methods: In the clinic, 20 control and 19 T1DM subjects were studied for 4 consecutive days. They underwent low-intensity PA sessions daily. PA was tracked by the PA monitoring system (PAMS), a system comprising accelerometers and inclinometers. Variations on glucose dynamics were tracked estimating first- and second-order time derivatives of glucose concentration from CGM via Bayesian smoothing. Short-time effects of PA on glucose dynamics were quantified through the partial correlation function in the interval (0, 60 min) after starting PA. Results: C...
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paper_title: An Integrated Multivariable Artificial Pancreas Control System

paper_content:

The objective was to develop a closed-loop (CL) artificial pancreas (AP) control system that uses continuous measurements of glucose concentration and physiological variables, integrated with a hypoglycemia early alarm module to regulate glucose concentration and prevent hypoglycemia. Eleven open-loop (OL) and 9 CL experiments were performed. A multivariable adaptive artificial pancreas (MAAP) system was used for the first 6 CL experiments. An integrated multivariable adaptive artificial pancreas (IMAAP) system consisting of MAAP augmented with a hypoglycemia early alarm system was used during the last 3 CL experiments. Glucose values and physical activity information were measured and transferred to the controller every 10 minutes and insulin suggestions were entered to the pump manually. All experiments were designed to be close to real-life conditions. Severe hypoglycemic episodes were seen several times during the OL experiments. With the MAAP system, the occurrence of severe hypoglycemia was decreased significantly (P < .01). No hypoglycemia was seen with the IMAAP system. There was also a significant difference (P < .01) between OL and CL experiments with regard to percentage of glucose concentration (54% vs 58%) that remained within target range (70-180 mg/dl). Integration of an adaptive control and hypoglycemia early alarm system was able to keep glucose concentration values in target range in patients with type 1 diabetes. Postprandial hypoglycemia and exercise-induced hypoglycemia did not occur when this system was used. Physical activity information improved estimation of the blood glucose concentration and effectiveness of the control system.
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paper_title: Physical Activity—The Major Unaccounted Impediment to Closed Loop Control

paper_content:

This article presents a mathematical model of glucose homeostasis that is valid during physical activity. Known changes in glucose dynamics during exercise were accounted for in the model, and exercise itself was detected and quantified through heart rate (beats per minute). The model was successfully fit to 21 type 1 diabetic subjects during a hyperinsulemic clamp protocol, and performance of the new model was compared with the standard minimal model of glucose kinetics that it was derived from.
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paper_title: Characteristics of a multisensor system for non invasive glucose monitoring with external validation and prospective evaluation

paper_content:

The Multisensor Glucose Monitoring System (MGMS) features non invasive sensors for dielectric characterisation of the skin and underlying tissue in a wide frequency range (1kHz-100MHz, 1 and 2GHz) as well as optical characterisation. In this paper we describe the results of using an MGMS in a miniaturised housing with fully integrated sensors and battery. Six patients with Type I Diabetes Mellitus (age 44+/-16y; BMI 24.1+/-1.3kg/m(2), duration of diabetes 27+/-12y; HbA1c 7.3+/-1.0%) wore a single Multisensor at the upper arm position and performed a total of 45 in-clinic study days with 7 study days per patient on average (min. 5 and max. 10). Glucose changes were induced either orally or by i.v. glucose administration and the blood glucose was measured routinely. Several prospective data evaluation routines were applied to evaluate the data. The results are shown using one of the restrictive data evaluation routines, where measurements from the first 22 study days were used to train a linear regression model. The global model was then prospectively applied to the data of the remaining 23 study days to allow for an external validation of glucose prediction. The model application yielded a Mean Absolute Relative Difference of 40.8%, a Mean Absolute Difference of 51.9mgdL(-1), and a correlation of 0.84 on average per study day. The Clarke error grid analyses showed 89.0% in A+B, 4.5% in C, 4.6% in D and 1.9% in the E region. Prospective application of a global, purely statistical model, demonstrates that glucose variations can be tracked non invasively by the MGMS in most cases under these conditions.
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paper_title: Chemical bionics - a novel design approach using Ion Sensitive Field Effect Transistors

paper_content:

This paper introduces Chemical Bionics in which the biochemical physiology of cells in the body are implemented in VLSI to make novel bio-inspired therapeutic devices. As an example, the glucose dependant electrophysiology of the pancreatic beta cell is implemented in silicon to form a novel bio-inspired prosthetic for glucose homeostasis of Type I diabetes. For this, the Ion Sensitive Field Effect Transistor (ISFET) is shown as a suitable chemical sensing front end, which allows CMOS monolithic implementation, as well as low power weak-inversion operation.
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paper_title: Regularised Model Identification Improves Accuracy of Multisensor Systems for Noninvasive Continuous Glucose Monitoring in Diabetes Management

paper_content:

Continuous glucose monitoring (CGM) by suitable portable sensors plays a central role in the treatment of diabetes, a disease currently affecting more than 350 million people worldwide. Noninvasive CGM (NI-CGM), in particular, is appealing for reasons related to patient comfort (no needles are used) but challenging. NI-CGM prototypes exploiting multisensor approaches have been recently proposed to deal with physiological and environmental disturbances. In these prototypes, signals measured noninvasively (e.g., skin impedance, temperature, optical skin properties, etc.) are combined through a static multivariate linear model for estimating glucose levels. In this work, by exploiting a dataset of 45 experimental sessions acquired in diabetic subjects, we show that regularisation-based techniques for the identification of the model, such as the least absolute shrinkage and selection operator (better known as LASSO), Ridge regression, and Elastic-Net regression, improve the accuracy of glucose estimates with respect to techniques, such as partial least squares regression, previously used in the literature. More specifically, the Elastic-Net model (i.e., the model identified using a combination of and norms) has the best results, according to the metrics widely accepted in the diabetes community. This model represents an important incremental step toward the development of NI-CGM devices effectively usable by patients.
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paper_title: Ion-Sensitive Field-Effect Transistor for Biological Sensing

paper_content:

In recent years there has been great progress in applying FET-type biosensors for highly sensitive biological detection. Among them, the ISFET (ion-sensitive field-effect transistor) is one of the most intriguing approaches in electrical biosensing technology. Here, we review some of the main advances in this field over the past few years, explore its application prospects, and discuss the main issues, approaches, and challenges, with the aim of stimulating a broader interest in developing ISFET-based biosensors and extending their applications for reliable and sensitive analysis of various biomolecules such as DNA, proteins, enzymes, and cells.
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paper_title: Non-invasive continuous glucose monitoring: improved accuracy of point and trend estimates of the Multisensor system

paper_content:

Non-invasive continuous glucose monitoring (NI-CGM) sensors are still at an early stage of development, but, in the near future, they could become particularly appealing in diabetes management. Solianis Monitoring AG (Zurich, Switzerland) has proposed an approach for NI-CGM based on a multi-sensor concept, embedding primarily dielectric spectroscopy and optical sensors. This concept requires a mathematical model able to estimate glucose levels from the 150 channels directly measured through the Multisensor. A static multivariate linear regression model (with order and parameters common to the entire population of subjects) was proposed for such a scope (Caduff et al., Biosens Bioelectron 26:3794–3800, 2011). The aim of this work is to evaluate the accuracy in the estimation of glucose levels and trends that the NI-CGM Multisensor platform can achieve by exploiting different techniques for model identification, namely, ordinary least squares, subset variable selection, partial least squares and least absolute shrinkage and selection operator (LASSO). Data collected in human beings monitored for a total of 45 study days were used for model identification and model test. Several metrics of standard use in the diabetes scientific community to measure point and clinical accuracy of glucose sensors were used to assess the models. Results indicate that the LASSO technique is superior to the others shrinking many channel weights to zero thus leading to smoother glucose profiles and resulting in a more robust model to possible artifacts in the Multisensor data. Although, as expected, the performance of the NI-CGM system with the LASSO model is not yet comparable with that of enzyme-based needle glucose sensors, glucose trends are satisfactorily estimated. Considering the non-invasive nature of the multi-sensor platform, this result can have an immediate impact in the current clinical practice, e.g., to integrate sparse self-monitoring of blood glucose data with an indication of the glucose trend to aid the diabetic patient in dealing with, or even preventing in the short time scale, the threats of critical events such as hypoglycaemia.
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paper_title: Sensium: an ultra-low-power wireless body sensor network platform: Design & application challenges

paper_content:

In this paper we present a system-on-chip for wireless body sensor networks, which integrates a transceiver, hardware MAC protocol, microprocessor, IO peripherals, memories, ADC and custom sensor interfaces. Addressing the challenges in the design, this paper will continue to discuss the issues in the applications of this technology to body worn monitoring for real-time measurement of ECG, heart rate, physical activity, respiration and/or skin temperature. Two application challenges are described; the real-time measurement of energy expenditure using the LifePebble, and; the development issues surrounding the ‘Digital Patch’.
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paper_title: Non-Invasive Continuous Glucose Monitoring with Multi-Sensor Systems: A Monte Carlo-Based Methodology for Assessing Calibration Robustness

paper_content:

In diabetes research, non-invasive continuous glucose monitoring (NI-CGM) devices represent a new and appealing frontier. In the last years, some multi-sensor devices for NI-CGM have been proposed, which exploit several sensors measuring phenomena of different nature, not only for measuring glucose related signals, but also signals reflecting some possible perturbing processes (temperature, blood perfusion). Estimation of glucose levels is then obtained combining these signals through a mathematical model which requires an initial calibration step exploiting one reference blood glucose (RBG) sample. Even if promising results have been obtained, especially in hospitalized volunteers, at present the temporal accuracy of NI-CGM sensors may suffer because of environmental and physiological interferences. The aim of this work is to develop a general methodology, based on Monte Carlo (MC) simulation, to assess the robustness of the calibration step used by NI-CGM devices against these disturbances. The proposed methodology is illustrated considering two examples: the first concerns the possible detrimental influence of sweat events, while the second deals with calibration scheduling. For implementing both examples, 45 datasets collected by the Solianis Multisensor system are considered. In the first example, the MC methodology suggests that no further calibration adjustments are needed after the occurrence of sweat events, because the “Multisensor+model” system is able to deal with the disturbance. The second case study shows how to identify the best time interval to update the model's calibration for improving the accuracy of the estimated glucose. The methodology proposed in this work is of general applicability and can be helpful in making those incremental steps in NI-CGM devices development needed to further improve their performance.
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paper_title: An Integrated Multivariable Artificial Pancreas Control System

paper_content:

The objective was to develop a closed-loop (CL) artificial pancreas (AP) control system that uses continuous measurements of glucose concentration and physiological variables, integrated with a hypoglycemia early alarm module to regulate glucose concentration and prevent hypoglycemia. Eleven open-loop (OL) and 9 CL experiments were performed. A multivariable adaptive artificial pancreas (MAAP) system was used for the first 6 CL experiments. An integrated multivariable adaptive artificial pancreas (IMAAP) system consisting of MAAP augmented with a hypoglycemia early alarm system was used during the last 3 CL experiments. Glucose values and physical activity information were measured and transferred to the controller every 10 minutes and insulin suggestions were entered to the pump manually. All experiments were designed to be close to real-life conditions. Severe hypoglycemic episodes were seen several times during the OL experiments. With the MAAP system, the occurrence of severe hypoglycemia was decreased significantly (P < .01). No hypoglycemia was seen with the IMAAP system. There was also a significant difference (P < .01) between OL and CL experiments with regard to percentage of glucose concentration (54% vs 58%) that remained within target range (70-180 mg/dl). Integration of an adaptive control and hypoglycemia early alarm system was able to keep glucose concentration values in target range in patients with type 1 diabetes. Postprandial hypoglycemia and exercise-induced hypoglycemia did not occur when this system was used. Physical activity information improved estimation of the blood glucose concentration and effectiveness of the control system.
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paper_title: GUDM: Automatic Generation of Unified Datasets for Learning and Reasoning in Healthcare

paper_content:

A wide array of biomedical data are generated and made available to healthcare experts. However, due to the diverse nature of data, it is difficult to predict outcomes from it. It is therefore necessary to combine these diverse data sources into a single unified dataset. This paper proposes a global unified data model (GUDM) to provide a global unified data structure for all data sources and generate a unified dataset by a “data modeler” tool. The proposed tool implements user-centric priority based approach which can easily resolve the problems of unified data modeling and overlapping attributes across multiple datasets. The tool is illustrated using sample diabetes mellitus data. The diverse data sources to generate the unified dataset for diabetes mellitus include clinical trial information, a social media interaction dataset and physical activity data collected using different sensors. To realize the significance of the unified dataset, we adopted a well-known rough set theory based rules creation process to create rules from the unified dataset. The evaluation of the tool on six different sets of locally created diverse datasets shows that the tool, on average, reduces 94.1% time efforts of the experts and knowledge engineer while creating unified datasets.
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paper_title: A systematic review of telemedicine interventions to support blood glucose self-monitoring in diabetes

paper_content:

Aims To evaluate evidence for feasibility, acceptability and cost-effectiveness of diabetes telemedicine applications. Methods MEDLINE , EMBASE , PSYCHINFO , CINAHL , Cochrane, and INSPEC were searched using the terms diabetes and telemedicine for clinical studies using electronic transfer of blood glucose results in people with diabetes. The technology used, trial design and clinical outcome measures used were extracted for trials and prospective cohort studies. Randomized controlled trials with HbA 1c as an outcome were pooled using standard meta-analytical methods. Results We identified 539 papers among which 32 papers described 10 prospective cohort studies, 12 parallel group randomized controlled trials (RCT), three crossover trials, and one non-parallel group trial. Only two studies described full details of randomization, blinding of outcomes and dropouts and withdrawals. Electronic transfer of glucose results appears feasible in a clinical setting. Only two of the RCTs included more than 100 patients, and only three extended to 1 year. Only one study was designed to show that telemedicine interventions might replace clinic interventions without deterioration in HbA 1c . Results pooled from the nine RCTs with reported data did not provide evidence that the interventions were effective in reducing HbA 1c ( − 0.1%, 95% CI − 0.4% to 0.04%). Conclusions Telemedicine solutions for diabetes care are feasible and acceptable, but evidence for their effectiveness in improving HbA 1c or reducing costs while maintaining HbA 1c levels, or improving other aspects of diabetes management is not strong. Further research should seek to understand how telemedicine might enhance educational and self-management interventions and RCTs are required to examine cost-effectiveness.
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paper_title: Are patients with diabetes mellitus satisfied with technologies used to assist with diabetes management and coping?: A structured review.

paper_content:

Modern technological devices supporting coping and management for patients with diabetes are increasingly popular and could be important healthcare tools. This review aimed to evaluate patient satisfaction and perceptions regarding these devices, examples of which include short message service reminder systems, online educational programs, and clinician-patient electronic communication. Therapy devices such as continuous glucose monitors and continuous subcutaneous insulin infusion pumps are not included in this review. Embase, Psychinfo, Medline, CINAHL, and gray literature databases were searched for "diabetes mellitus," "technical device," "patient satisfaction," and their synonyms. This review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement guidelines. The search produced 1,902 studies, 26 of which were included in the review: type 1 diabetes mellitus (eight studies), type 2 diabetes mellitus (nine studies), and both (nine studies). High satisfaction was seen with almost all devices and correlated strongly with ease of use and improved diabetes management. Satisfaction was not affected by participant age, and the effect of diabetes type was not assessed. Web devices were reported as easiest to use. Increased support was valued and resulted from devices facilitating interaction with healthcare professionals (HCPs) or peers. Technical difficulties were barriers to both use and satisfaction. Overall, patients enjoyed supplementing their usual therapy with these devices. Perceived support from HCPs or peers formed an important aspect of patient satisfaction and should be considered for future interventions.
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paper_title: Health Technologies for Monitoring and Managing Diabetes: A Systematic Review

paper_content:

Background: The primary objective of this review was to determine the strength of evidence for the effectiveness of selfmonitoring devices and technologies for individuals with type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM) based on specific health-related outcome measures. Self-monitoring devices included those that assist patients with managing diabetes and preventing cardiovascular complications (CVCs). A secondary objective was to explore issues of feasibility, usability, and compliance among patients and providers. Methods: Study criteria included individuals ≥14 years and youth (7–14 years) with T1DM or T2DM, intervention with a self-monitoring device, assessment of clinical outcomes with the device, literature in English, and ≥10 participants. Relevant published literature was searched from 1985 to 2008. Randomized controlled trials and observational studies were included. Data were extracted for clinical outcomes, feasibility and compliance methods, and results. Selected studies were independently evaluated with a validated instrument for assessing methodological quality. Results: Eighteen trials were selected. Predominant types of device interventions included self-monitoring of blood glucose, pedometers, and cell phone or wireless technologies. Feasibility and compliance were measured in the majority of studies. Conclusions: Self-monitoring of blood glucose continues to be an effective tool for the management of diabetes. Wireless technologies can improve diabetes self-care, and pedometers are effective lifestyle modification tools. The results of this review indicate a need for additional controlled trial research on existing and novel technologies for diabetes self-monitoring, on health outcomes associated with diabetes and CVCs, and device feasibility and compliance.
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paper_title: A systematic review of IT for diabetes self-management: Are we there yet?

paper_content:

BACKGROUND ::: Recent advances in information technology (IT) coupled with the increased ubiquitous nature of information technology (IT) present unique opportunities for improving diabetes self-management. The objective of this paper is to determine, in a systematic review, how IT has been used to improve self-management for adults with Type 1 and Type 2 diabetes. ::: ::: ::: METHODS ::: The review covers articles extracted from relevant databases using search terms related information technology and diabetes self-management published after 1970 until August 2012. Additional articles were extracted using the citation map in Web of Science. Articles representing original research describing the use of IT as an enabler for self-management tasks performed by the patient are included in the final analysis. ::: ::: ::: RESULTS ::: Overall, 74% of studies showed some form of added benefit, 13% articles showed no-significant value provided by IT, and 13% of articles did not clearly define the added benefit due to IT. Information technologies used included the Internet (47%), cellular phones (32%), telemedicine (12%), and decision support techniques (9%). Limitations and research gaps identified include usability, real-time feedback, integration with provider electronic medical record (EMR), as well as analytics and decision support capabilities. ::: ::: ::: CONCLUSION ::: There is a distinct need for more comprehensive interventions, in which several technologies are integrated in order to be able to manage chronic conditions such as diabetes. Such IT interventions should be theoretically founded and should rely on principles of user-centered and socio-technical design in its planning, design and implementation. Moreover, the effectiveness of self-management systems should be assessed along multiple dimensions: motivation for self-management, long-term adherence, cost, adoption, satisfaction and outcomes as a final result.
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paper_title: Self-management of Diabetes in Children and Young Adults Using Technology and Smartphone Applications

paper_content:

Treatment compliance and adherence are often a challenge in patients with type 1 diabetes, particularly for adolescent and young adult patients. With the availability of the internet and smart phone applications (apps) there is a hope that such technology could provide a means to encourage treatment adherence in this group of patients. This review focuses on whether telemedicine and smartphone technology in diabetes can influence self-management in young people with diabetes. A large number of smartphone apps are targeted at people with diabetes, but a limited number of welldesigned evaluation studies have been performed. As our review shows, the evidence base for efficacy of most of these applications is minimal and improvement in hard outcomes such as HbA1c and complication development is largely lacking.
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paper_title: Processing Diabetes Mellitus Composite Events in MAGPIE

paper_content:

The focus of this research is in the definition of programmable expert Personal Health Systems (PHS) to monitor patients affected by chronic diseases using agent oriented programming and mobile computing to represent the interactions happening amongst the components of the system. The paper also discusses issues of knowledge representation within the medical domain when dealing with temporal patterns concerning the physiological values of the patient. In the presented agent based PHS the doctors can personalize for each patient monitoring rules that can be defined in a graphical way. Furthermore, to achieve better scalability, the computations for monitoring the patients are distributed among their devices rather than being performed in a centralized server. The system is evaluated using data of 21 diabetic patients to detect temporal patterns according to a set of monitoring rules defined. The system's scalability is evaluated by comparing it with a centralized approach. The evaluation concerning the detection of temporal patterns highlights the system's ability to monitor chronic patients affected by diabetes. Regarding the scalability, the results show the fact that an approach exploiting the use of mobile computing is more scalable than a centralized approach. Therefore, more likely to satisfy the needs of next generation PHSs. PHSs are becoming an adopted technology to deal with the surge of patients affected by chronic illnesses. This paper discusses architectural choices to make an agent based PHS more scalable by using a distributed mobile computing approach. It also discusses how to model the medical knowledge in the PHS in such a way that it is modifiable at run time. The evaluation highlights the necessity of distributing the reasoning to the mobile part of the system and that modifiable rules are able to deal with the change in lifestyle of the patients affected by chronic illnesses.
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paper_title: Telemedicine Application in the Care of Diabetes Patients: Systematic Review and Meta-Analysis

paper_content:

BACKGROUND ::: The impact of telemedicine application on the management of diabetes patients is unclear, as the results are not consistent among different studies. The objective of this study is to conduct a systematic review and meta-analysis of randomized controlled trials (RCTs) assessing the impact of telemedicine interventions on change in hemoglobin A1c (HbA1c), blood pressure, LDL cholesterol (LDL-c) and body mass index (BMI) in diabetes patients. ::: ::: ::: METHODS ::: Electronic databases MEDLINE, Cochrane Central Register of Controlled Trials and LILACS were searched to identify relevant studies published until April 2012, supplemented by references from the selected articles. Study search and selection were performed by independent reviewers. Of the 6.258 articles retrieved, 13 RCTs (4207 patients) were included. Random effects model was applied to estimate the pooled results. ::: ::: ::: RESULTS ::: Telemedicine was associated with a statistically significant and clinically relevant absolute decline in HbA1c level compared to control (mean difference -0.44% [-4.8 mmol/mol] and 95% confidence interval [CI] -0.61 to -0.26% [-6.7 to -2.8 mmol/mol]; p<0.001). LDL-c was reduced in 6.6 mg/dL (95% CI -8.3 to -4.9; p<0.001), but the clinical relevance of this effect can be questioned. No effects of telemedicine strategies were seen on systolic (-1.6 mmHg and 95% CI -7.2 to 4.1) and diastolic blood pressure (-1.1 mmHg and 95% CI -3.0 to 0.8). The 2 studies that assessed the effect on BMI demonstrated a tendency of BMI reduction in favor of telemedicine. ::: ::: ::: CONCLUSIONS ::: Telemedicine strategies combined to the usual care were associated with improved glycemic control in diabetic patients. No clinical relevant impact was observed on LDL-c and blood pressure, and there was a tendency of BMI reduction in diabetes patients who used telemedicine, but these outcomes should be further explored in future trials.
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paper_title: Smart wearable systems: Current status and future challenges

paper_content:

Objective: Extensive efforts have been made in both academia and industry in the research and development of smart wearable systems (SWS) for health monitoring (HM). Primarily influenced by skyrocketing healthcare costs and supported by recent technological advances in micro- and nanotechnologies, miniaturisation of sensors, and smart fabrics, the continuous advances in SWS will progressively change the landscape of healthcare by allowing individual management and continuous monitoring of a patient's health status. Consisting of various components and devices, ranging from sensors and actuators to multimedia devices, these systems support complex healthcare applications and enable low-cost wearable, non-invasive alternatives for continuous 24-h monitoring of health, activity, mobility, and mental status, both indoors and outdoors. Our objective has been to examine the current research in wearable to serve as references for researchers and provide perspectives for future research. Methods: Herein, we review the current research and development of and the challenges facing SWS for HM, focusing on multi-parameter physiological sensor systems and activity and mobility measurement system designs that reliably measure mobility or vital signs and integrate real-time decision support processing for disease prevention, symptom detection, and diagnosis. For this literature review, we have chosen specific selection criteria to include papers in which wearable systems or devices are covered. Results: We describe the state of the art in SWS and provide a survey of recent implementations of wearable health-care systems. We describe current issues, challenges, and prospects of SWS. Conclusion: We conclude by identifying the future challenges facing SWS for HM.
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paper_title: Wearable Medical Systems for p-Health

paper_content:

Driven by the growing aging population, prevalence of chronic diseases, and continuously rising healthcare costs, the healthcare system is undergoing a fundamental transformation, from the conventional hospital-centered system to an individual-centered system. Current and emerging developments in wearable medical systems will have a radical impact on this paradigm shift. Advances in wearable medical systems will enable the accessibility and affordability of healthcare, so that physiological conditions can be monitored not only at sporadic snapshots but also continuously for extended periods of time, making early disease detection and timely response to health threats possible. This paper reviews recent developments in the area of wearable medical systems for p-Health. Enabling technologies for continuous and noninvasive measurements of vital signs and biochemical variables, advances in intelligent biomedical clothing and body area networks, approaches for motion artifact reduction, strategies for wearable energy harvesting, and the establishment of standard protocols for the evaluation of wearable medical devices are presented in this paper with examples of clinical applications of these technologies.
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paper_title: MediCoordination: a practical approach to interoperability in the Swiss health system.

paper_content:

Interoperability and data exchange between partners in the health sector is seen as one of the important domains that can improve care processes and in the long run also decrease costs of the health care system. Data exchange can assure that the data on the patient are as co mplete as possible avoiding potential mistreatments, and it can avoid double examinations if the data required are already available. On the other hand, health data is a sensible point for many people and strong protection needs to be implemented to protect patient data against misuse as well as tools to let the patient manage his/her own data. Many countries have eHealth initiatives in preparation or already implemented. However, health data exchange on a large scale still has a fairly long way to go as the political processes for global solutions are often complicated. In the MediCoordination project a prag matic approach is s elected trying to integrate several partners in health care on a regional scale. In parallel with the Swiss eHealth strategy that is currently being elaborated by the Swiss confederation, particularly medium-sized hospitals and external partners are targeted in MediCoordination to implement concrete added-value scenarios of inform ation exchange between hospitals and external medical actors.
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paper_title: An automated telemedicine system improves patient-reported well-being.

paper_content:

BACKGROUND ::: Control of serum glucose levels is essential for the reduction of complications of diabetes. Telemedicine is one strategy through which serum glucose control can be improved. ::: ::: ::: METHODS ::: A total of 35 adult, insulin-treated patients with diabetes (type 1 and type 2) were enrolled in the present study (63.0 +/- 10 years of age, 63% female) and randomized to telemedicine monitoring (including cordless, remote glucose monitor, and transmitter, n = 17), or conventional follow-up (n = 18). Metabolic parameters were evaluated, and a quality of life questionnaire was administered both pre- and post-treatment. ::: ::: ::: RESULTS ::: Groups were similar at baseline in terms of demographic, quality of life, and metabolic parameters. Significant differences in post-treatment metabolic parameters were not observed, although serum glucose was marginally elevated in the control group compared to the telemedicine group (214 +/- 65 mg/dL vs. 171 +/- 77 mg/dL, P = 0.09). On the other hand, being clinically symptom-free (71% vs. 11%, P = 0.003), having no hypoglycemic events (82% vs. 17%, P = 0.0001), and having no hyperglycemic events (65% vs. 17%, P = 0.004) were all significantly more frequently reported in the telemedicine group compared to the control group. Compared to the control group, the telemedicine group reported experiencing significantly less anxiety, treatment difficulty, depression, disease-associated life complications, and feelings of impotence or ineptitude and significantly greater improvement in personal control over glucose, weight, and overall diabetes. ::: ::: ::: CONCLUSIONS ::: Though post-treatment metabolic differences were not observed between treatment groups, the telemedicine group reported significantly greater post-treatment experiences of improved quality of life and sense of control over the disease. Thus patient satisfaction can be enhanced through the use of telemedicine.
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paper_title: Mobile Health Applications to Assist Patients with Diabetes: Lessons Learned and Design Implications

paper_content:

We expect that the following elements will be important in future FTA designs: (A) automatic data transfer when possible; (B) motivational and visual user interfaces; (C) apps with considerable health benefits in relation to the effort required; (D) dynamic usage, e.g., both personal and together with HC personnel, long-/short-term perspective; and (E) inclusion of context sensitivity in apps. We conclude that mHealth apps will empower patients to take a more active role in managing their own health.
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paper_title: Mobile Intervention Design in Diabetes: Review and Recommendations

paper_content:

Mobile technology enhances the potential to assess, prompt, educate, and engage individuals with diabetes. The near-ubiquitous presence of mobile phones allows real-time contextually relevant support for diabetes self-care. We review the design of mobile interventions included in a recent meta-analysis. Although mobile programs can lead to improvements in glycemic control, many aspects, such as the role of the diabetes clinician, real-time features, and patient engagement have not been documented. Studies with the greatest impact on hemoglobin A1c integrated patient feedback and a role for clinicians. Research is needed regarding feasible and efficacious roles for clinical support in mobile interventions. Recommendations for design and research include the following: consideration of patient and clinician burden; identification of patterns and metrics for patient treatment adherence and engagement; integration of goal setting and problem solving; enhancing patient education; a greater focus on patient-centered motivational strategies; and utilization of study designs that relate intervention design elements to outcomes.
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paper_title: The Impact of Mobile Monitoring Technologies on Glycosylated Hemoglobin in Diabetes: A Systematic Review

paper_content:

Background: A new development in the field of telehealth is the use of mobile health technologies (mhealth) to help patients record and track medical information. Mhealth appears particularly advantageous for conditions that require intense and ongoing monitoring, such as diabetes, and where people are of working age and not disabled. This review aims to evaluate the evidence for the effectiveness of mhealth interventions in diabetes management on glycosylated hemoglobin. Method: A comprehensive search strategy was developed and applied to eight electronic databases to identify studies that investigated the clinical effectiveness of mobile-based applications that allowed patients to record and send their blood glucose readings to a central server. The eligibility of 8543 papers was assessed against the selection criteria, and 24 papers were reviewed. All studies reviewed were assessed for quality using a standardized quality assessment tool. Results: Results for patients with type 1 and type 2 diabetes were examined separately. Study variability and poor reporting made comparison difficult, and most studies had important methodological weaknesses. Evidence on the effectiveness of mhealth interventions for diabetes was inconsistent for both types of diabetes and remains weak.
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Title: Sensor Monitoring of Physical Activity to Improve Glucose Management in Diabetic Patients: A Review

Section 1: Introduction
Description 1: Provide an overview of the importance of glucose monitoring for diabetic patients, traditional monitoring methods, and the development and limitations of CGM and NI-CGM technologies.

Section 2: Glucose Dynamic during Sensor-Monitored Physical Exercise
Description 2: Discuss the relationship between physical activity and glucose dynamics, and the impact of physical exercise on glucose levels in T1DM patients as determined by biosensors.

Section 3: Sensors Estimating Glucose Level Based on Physical Activity Signals
Description 3: Describe devices that estimate glucose concentration directly from physiological parameters related to physical activity, the technologies and methodologies used, and their effectiveness in controlled settings and daily life.

Section 4: Integration of Sensors-Based Physiological Parameters with CGM Data
Description 4: Explore how physiological data from physical activity sensors can be integrated with CGM data to improve glucose level prediction accuracy and prevent hypoglycemia during physical exercise.

Section 5: Integration of Sensors-Based Physiological Parameters with NI-CGM
Description 5: Investigate the potential for enhancing the accuracy of NI-CGM through the integration of various physiological parameters and the effectiveness of these combined systems in everyday conditions and during exercise.

Section 6: Conclusions
Description 6: Summarize the potential benefits of combining physiological monitoring devices with glucose tracking technologies, discuss gaps and areas for future research, and consider the role of ICT and patient satisfaction with new monitoring technologies.