Research on human gait sensing based on triboelectric nanogenerator

Gang Yang, Lifang Wang, Jiayun Tian
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Abstract

To address the problem of frequent battery replacement for wearable sensors applied to fall detection among the elderly, a portable and low-cost triboelectric nanogenerator (TENG)-based self-powered sensor for human gait monitoring is proposed. The main fabrication materials of the TENG are polytetrafluoroethylene (PTFE) film, aluminum (Al) foil, and polyimide (PI) film, where PTFE and Al are the friction layer materials and the PI film is used to improve the output performance. Exploiting the ability of TENGs to monitor changes in environmental conditions, a self-powered sensor based on the TENG is placed in an insole to collect gait information. Since a TENG does not require a power source to convert physical and mechanical signals into electrical signals, the electrical signals can be used as sensing signals to be analyzed by a computer to recognize daily human activities and fall status. Experimental results show that the accuracy of the TENG-based sensor for recognizing human gait is 97.2%, demonstrating superior sensing performance and providing valuable insights for future monitoring of fall events in the elderly population.
基于三电纳米发电机的人体步态传感研究
为了解决应用于老年人跌倒检测的可穿戴传感器频繁更换电池的问题,我们提出了一种基于三电纳米发电机(TENG)的便携式低成本自供电传感器,用于人体步态监测。TENG 的主要制造材料为聚四氟乙烯(PTFE)薄膜、铝箔和聚酰亚胺(PI)薄膜,其中 PTFE 和 Al 为摩擦层材料,PI 薄膜用于提高输出性能。利用 TENG 监测环境条件变化的能力,将基于 TENG 的自供电传感器置于鞋垫中,以收集步态信息。由于 TENG 无需电源即可将物理和机械信号转换为电信号,因此电信号可用作传感信号,由计算机进行分析,以识别人体的日常活动和跌倒状态。实验结果表明,基于 TENG 的传感器识别人体步态的准确率为 97.2%,显示出卓越的传感性能,为未来监测老年人群的跌倒事件提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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