Engagement-Free and Contactless Bed Occupancy and Vital Signs Monitoring

• Published in: IEEE internet of things journal Vol. 11; no. 5; pp. 7935 - 7947
• Main Authors: Song, Yingjian, Li, Bingnan, Luo, Dan, Xie, Zaipeng, Phillips, Bradley G., Ke, Yuan, Song, Wenzhan
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.03.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Bed occupancy; Contactless Monitoring; Estimation; Feature extraction; Heart beat; Heart rate; heart rate (HR); interbeat interval (IBI); Monitoring; Motion perception; Quality assessment; Respiratory rate; respiratory rate (RR); Signal processing; Signal quality; sleep; Sleep apnea; Telemedicine; Vibrations; vital Signs; sleep; heart rate; Vital Signs; bed occupancy; respiratory rate; Contactless Monitoring; inter-beat interval
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2023.3316674

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.