Engagement-Free and Contactless Bed Occupancy and Vital Signs Monitoring

This article presents the design and evaluation of an engagement-free and contactless vital signs and occupancy monitoring system called BedDot. While many existing works demonstrated contactless vital signs estimation, they do not address the practical challenge of environment noises, online bed occupancy detection, and data quality assessment in the real-world environment. This work presents a robust signal quality assessment algorithm consisting of three parts: 1) bed occupancy detection; 2) movement detection; and 3) heartbeat detection, to identify high-quality data. It also presents a series of innovative vital signs estimation algorithms that leverage the advanced signal processing and Bayesian theorem for contactless heart rate (HR), respiratory rate (RR), and interbeat interval (IBI) estimation. The experimental results demonstrate that BedDot achieves over 99% accuracy for bed occupancy detection, and MAE of 1.38 BPM, 1.54 BPM, and 24.84 ms for HR, RR, and IBI estimation, respectively, compared with an FDA-approved device. The BedDot system has been extensively tested with data collected from 75 subjects for more than 80 h under different conditions, demonstrating its generalizability across different people and environments.