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Background: Monitoring glucose excursions is important in diabetes management. This can be achieved using continuous glucose monitors (CGMs). However, CGMs are expensive and invasive. Thus, alternative low-cost noninvasive wearable sensors capable of predicting glycemic excursions could be a game changer to manage diabetes. Methods: In this article, we explore two noninvasive sensor modalities, electrocardiograms (ECGs) and accelerometers, collected on five healthy participants over two weeks, to predict both hypoglycemic and hyperglycemic excursions. We extract 29 features encompassing heart rate variability features from the ECG, and time- and frequency-domain features from the accelerometer. We evaluated two machine-learning approaches to predict glycemic excursions: a classification model and a regression model. Results: The best model for both hypoglycemia and hyperglycemia detection was the regression model based on ECG and accelerometer data, yielding 76% sensitivity and specificity for hypoglycemia and 79% sensitivity and specificity for hyperglycemia. This had an improvement of 5% in sensitivity and specificity for both hypoglycemia and hyperglycemia when compared with using ECG data alone. Conclusions: Electrocardiogram is a promising alternative not only to detect hypoglycemia but also to predict hyperglycemia. Supplementing ECG data with contextual information from accelerometer data can improve glucose prediction. 

Wearable devices for continuous monitoring of arterial pulse waves have the potential to improve the diagnosis, prognosis, and management of cardiovascular diseases. These pulse wave signals are often affected by the contact pressure between the wearable device and the skin, limiting the accuracy and reliability of hemodynamic parameter quantification. Here, a continuous hemodynamic monitoring device that enables the simultaneous recording of dual‐channel bioimpedance and quantification of pulse wave velocity (PWV) and blood pressure (BP) is reported. The investigations demonstrate the effect of contact pressure on bioimpedance and PWV. The pulsatile bioimpedance magnitude reached its maximum when the contact pressure approximated the mean arterial pressure of the subject. PWV is employed to continuously quantify BP while maintaining comfortable contact pressure for prolonged wear. The mean absolute error and standard deviation of the error compared to the reference value are determined to be 0.1 ± 3.3 mmHg for systolic BP, 1.3 ± 3.7 mmHg for diastolic BP, and −0.4 ± 3.0 mmHg for mean arterial pressure when measurements are conducted in the lying down position. This research demonstrates the potential of wearable dual‐bioimpedance sensors with contact pressure guidance for reliable and continuous hemodynamic monitoring.

 

Continuous monitoring of arterial blood pressure is clinically important for diagnosing and managing cardiovascular diseases. Soft electronic devices with skin‐like properties show promise in various applications, including the human‐machine interface, the Internet of Things, and health monitoring. Herein, the use of add‐on soft electronic interfaces addresses the connection challenges between soft electrodes and rigid data acquisition circuitry for bioimpedance monitoring of cardiac signals, including heart rate and cuffless blood pressure is reported. Nanocomposite films in add‐on electrodes provide robust electrical and mechanical contact with the skin and the rigid circuitry. Bioimpedance sensors composed of add‐on electrodes offer continuous blood pressure monitoring with high accuracy. Specifically, the bioimpedance collected with add‐on nanocomposite electrodes shows a signal‐to‐noise ratio of 37.0 dB, higher than the ratio of 25.9 dB obtained with standard silver/silver chloride (Ag/AgCl) gel electrodes. Although the sample set is low, the continuously measured systolic and diastolic blood pressure offer accuracy of −2.0 ± 6.3 mmHg and −4.3 ± 3.9 mmHg, respectively, confirming the grade A performance based on the IEEE standard. These results show promise in bioimpedance measurements with add‐on soft electrodes for cuffless blood pressure monitoring.