A Contactless Health Monitoring System for Vital Signs Monitoring, Human Activity Recognition, and Tracking

被引:5
|
作者
Li, Anna [1 ]
Bodanese, Eliane [2 ]
Poslad, Stefan [2 ]
Chen, Penghui [3 ]
Wang, Jun [3 ]
Fan, Yonglei [2 ]
Hou, Tianwei [4 ,5 ]
机构
[1] Univ Lancaster, Sch Comp & Commun, Lancaster LA1 4WA, England
[2] Queen Mary Univ London, Sch Elect Engn & Comp Sci, London E1 4NS, England
[3] Beihang Univ, Sch Elect Informat Engn, Beijing 100190, Peoples R China
[4] Beijing Jiaotong Univ, Sch Elect & Informat Engn, Beijing 100044, Peoples R China
[5] Friedrich Alexander Univ Erlangen Nurnberg, Inst Digital Commun, D-91054 Erlangen, Germany
来源
IEEE INTERNET OF THINGS JOURNAL | 2024年 / 11卷 / 18期
关键词
Deep learning; integrated sensing and communication (ISAC); radar; remote health monitoring; DIAGNOSIS;
D O I
10.1109/JIOT.2023.3336232
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:29275 / 29286
页数:12
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