Automated detection of sensor detachments for physiological sensing in the wild

Abstract

Body area sensor networks measure biomedical signals from subjects continuously, as they go about their daily lives. Signals measured in these conditions are affected by anomalies, such as artifacts and noise. Some anomalies can be corrected, if detected in real-time, for example, ECG electrode detachment. We present energy and computationally efficient algorithms for the detection of sensor detachment, developed for the AutoSense system.