Li A, Bodanese E, Poslad S, Chen P, Wang J, Fan Y, Hou T (2024)
Publication Type: Journal article
Publication year: 2024
Book Volume: 11
Pages Range: 29275-29286
Journal Issue: 18
DOI: 10.1109/JIOT.2023.3336232
Integrated sensing and communication technologies provide essential sensing capabilities that address pressing challenges in remote health monitoring systems. However, most of today's systems remain obtrusive, requiring users to wear devices, interfering with people's daily activities, and often raising privacy concerns. Herein, we present HealthDAR, a low-cost, contactless, and easy-to-deploy health monitoring system. Specifically, HealthDAR encompasses three interventions: 1) symptom early detection (monitoring of vital signs and cough detection); 2) tracking and social distancing; and 3) preventive measures (monitoring of daily activities, such as face-touching and hand-washing). HealthDAR has three key components: 1) a low-cost, low-energy, and compact integrated radar system; 2) a simultaneous signal processing combined deep learning (SSPDL) network for cough detection; and 3) a deep learning method for the classification of daily activities. Through performance tests involving multiple subjects across uncontrolled environments, we demonstrate HealthDAR's practical utility for health monitoring.
APA:
Li, A., Bodanese, E., Poslad, S., Chen, P., Wang, J., Fan, Y., & Hou, T. (2024). A Contactless Health Monitoring System for Vital Signs Monitoring, Human Activity Recognition, and Tracking. IEEE Internet of Things, 11(18), 29275-29286. https://doi.org/10.1109/JIOT.2023.3336232
MLA:
Li, Anna, et al. "A Contactless Health Monitoring System for Vital Signs Monitoring, Human Activity Recognition, and Tracking." IEEE Internet of Things 11.18 (2024): 29275-29286.
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