Design of flexible wearable sensing systems.
10.7507/1001-5515.202208012
- Author:
Hongyu CHEN
1
;
Zaihao WANG
2
;
Long MENG
2
;
Ke XU
3
;
Zeyu WANG
3
;
Chen CHEN
4
;
Wei CHEN
1
Author Information
1. Greater Bay Area Institute of Precision Medicine, Guangzhou 511466, P. R. China.
2. Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, P. R. China.
3. Imperial College London, London SW7 2AZ, UK.
4. Human Phenome Institute, Fudan University, Shanghai 201203, P. R. China.
- Publication Type:Journal Article
- Keywords:
Body sensing network;
Flexible wearable;
Motion signal monitoring;
Physiological signal monitoring
- MeSH:
Humans;
Aged;
Monitoring, Physiologic/methods*;
Wearable Electronic Devices;
Chronic Disease
- From:
Journal of Biomedical Engineering
2023;40(6):1071-1083
- CountryChina
- Language:Chinese
-
Abstract:
The aging population and the increasing prevalence of chronic diseases in the elderly have brought a significant economic burden to families and society. The non-invasive wearable sensing system can continuously and real-time monitor important physiological signs of the human body and evaluate health status. In addition, it can provide efficient and convenient information feedback, thereby reducing the health risks caused by chronic diseases in the elderly. A wearable system for detecting physiological and behavioral signals was developed in this study. We explored the design of flexible wearable sensing technology and its application in sensing systems. The wearable system included smart hats, smart clothes, smart gloves, and smart insoles, achieving long-term continuous monitoring of physiological and motion signals. The performance of the system was verified, and the new sensing system was compared with commercial equipment. The evaluation results demonstrated that the proposed system presented a comparable performance with the existing system. In summary, the proposed flexible sensor system provides an accurate, detachable, expandable, user-friendly and comfortable solution for physiological and motion signal monitoring. It is expected to be used in remote healthcare monitoring and provide personalized information monitoring, disease prediction, and diagnosis for doctors/patients.
