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基于摩擦纳米发电机的智能可穿戴传感器用于个人健康监测。

Smart Wearable Sensors Based on Triboelectric Nanogenerator for Personal Healthcare Monitoring.

作者信息

Li Ruonan, Wei Xuelian, Xu Jiahui, Chen Junhuan, Li Bin, Wu Zhiyi, Wang Zhong Lin

机构信息

School of Chemistry and Chemical Engineering, Guangxi University, Nanning 530004, China.

Center on Nano-Energy Research, School of Physical Science & Technology, Guangxi University, Nanning 530004, China.

出版信息

Micromachines (Basel). 2021 Mar 25;12(4):352. doi: 10.3390/mi12040352.

Abstract

Accurate monitoring of motion and sleep states is critical for human health assessment, especially for a healthy life, early diagnosis of diseases, and medical care. In this work, a smart wearable sensor (SWS) based on a dual-channel triboelectric nanogenerator was presented for a real-time health monitoring system. The SWS can be worn on wrists, ankles, shoes, or other parts of the body and cloth, converting mechanical triggers into electrical output. By analyzing these signals, the SWS can precisely and constantly monitor and distinguish various motion states, including stepping, walking, running, and jumping. Based on the SWS, a fall-down alarm system and a sleep quality assessment system were constructed to provide personal healthcare monitoring and alert family members or doctors via communication devices. It is important for the healthy growth of the young and special patient groups, as well as for the health monitoring and medical care of the elderly and recovered patients. This work aimed to broaden the paths for remote biological movement status analysis and provide diversified perspectives for true-time and long-term health monitoring, simultaneously.

摘要

准确监测运动和睡眠状态对于人类健康评估至关重要,特别是对于健康生活、疾病的早期诊断和医疗护理而言。在这项工作中,提出了一种基于双通道摩擦纳米发电机的智能可穿戴传感器(SWS)用于实时健康监测系统。该SWS可以佩戴在手腕、脚踝、鞋子或身体和衣物的其他部位,将机械触发转换为电输出。通过分析这些信号,SWS可以精确且持续地监测和区分各种运动状态,包括踏步、行走、跑步和跳跃。基于SWS构建了跌倒报警系统和睡眠质量评估系统,以提供个人医疗保健监测,并通过通信设备向家庭成员或医生发出警报。这对于年轻人和特殊患者群体的健康成长,以及老年人和康复患者的健康监测和医疗护理都很重要。这项工作旨在拓宽远程生物运动状态分析的途径,并同时为实时和长期健康监测提供多样化的视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e727/8064435/f2c89d849090/micromachines-12-00352-g001.jpg

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