Chen Hongyu, Wang Zaihao, Meng Long, Xu Ke, Wang Zeyu, Chen Chen, Chen Wei
Greater Bay Area Institute of Precision Medicine, Guangzhou 511466, P. R. China.
Department of Electronic Engineering, School of Information Science and Technology, Fudan University, Shanghai 200438, P. R. China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2023 Dec 25;40(6):1071-1083. doi: 10.7507/1001-5515.202208012.
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.
人口老龄化以及老年人慢性病患病率的上升给家庭和社会带来了巨大的经济负担。非侵入式可穿戴传感系统能够持续实时监测人体重要生理体征并评估健康状况。此外,它还能提供高效便捷的信息反馈,从而降低老年人慢性病引发的健康风险。本研究开发了一种用于检测生理和行为信号的可穿戴系统。我们探索了柔性可穿戴传感技术的设计及其在传感系统中的应用。该可穿戴系统包括智能帽子、智能衣服、智能手套和智能鞋垫,实现了对生理和运动信号的长期连续监测。对系统性能进行了验证,并将新的传感系统与商用设备进行了比较。评估结果表明,所提出的系统与现有系统具有相当的性能。综上所述,所提出的柔性传感器系统为生理和运动信号监测提供了一种准确、可分离、可扩展、用户友好且舒适的解决方案。有望用于远程医疗监测,为医生/患者提供个性化信息监测、疾病预测和诊断。