Triboelectric gait sensing analysis system for self-powered IoT-based human motion monitoring

IF 22.7 1区 材料科学 Q1 MATERIALS SCIENCE, MULTIDISCIPLINARY
Infomat Pub Date : 2024-01-04 DOI:10.1002/inf2.12520
Leilei Zhao, Xiao Guo, Yusen Pan, Shouchuang Jia, Liqiang Liu, Walid A. Daoud, Peter Poechmueller, Xiya Yang
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引用次数: 0

Abstract

Quantitative analysis of gait parameters, such as stride frequency and step speed, is essential for optimizing physical exercise for the human body. However, the current electronic sensors used in human motion monitoring remain constrained by factors such as battery life and accuracy. This study developed a self-powered gait analysis system (SGAS) based on a triboelectric nanogenerator (TENG) fabricated electrospun composite nanofibers for motion monitoring and gait analysis for regulating exercise programs. The SGAS consists of a sensing module, a charging module, a data acquisition and processing module, and an Internet of Things (IoT) platform. Within the sensing module, two specialized sensing units, TENG-S1 and TENG-S2, are positioned at the forefoot and heel to generate synchronized signals in tandem with the user's footsteps. These signals are instrumental for real-time step count and step speed monitoring. The output of the two TENG units is significantly improved by systematically investigating and optimizing the electrospun composite nanofibers' composition, strength, and wear resistance. Additionally, a charge amplifier circuit is implemented to process the raw voltage signal, consequently bolstering the reliability of the sensing signal. This refined data is then ready for further reading and calculation by the micro-controller unit (MCU) during the signal transmission process. Finally, the well-conditioned signals are wirelessly transmitted to the IoT platform for data analysis, storage, and visualization, enhancing human motion monitoring.

Abstract Image

Abstract Image

用于自供电物联网人体运动监测的三电步态传感分析系统
步频和步速等步态参数的定量分析对于优化人体运动至关重要。然而,目前用于人体运动监测的电子传感器仍然受到电池寿命和精度等因素的限制。本研究开发了一种自供电步态分析系统(SGAS),该系统基于电纺复合纳米纤维制成的三电纳米发电机(TENG),用于运动监测和步态分析,以调节锻炼计划。SGAS 由传感模块、充电模块、数据采集和处理模块以及物联网(IoT)平台组成。在传感模块中,两个专门的传感单元 TENG-S1 和 TENG-S2 分别位于前脚掌和后脚跟处,与用户的脚步同步产生信号。这些信号有助于实时监测步数和步速。通过系统地研究和优化电纺复合纳米纤维的成分、强度和耐磨性,两个 TENG 单元的输出得到了显著改善。此外,还采用了电荷放大器电路来处理原始电压信号,从而提高了传感信号的可靠性。在信号传输过程中,微控制器单元(MCU)可进一步读取和计算这些细化数据。最后,经过处理的信号会以无线方式传输到物联网平台,用于数据分析、存储和可视化,从而加强对人体运动的监测。
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来源期刊
Infomat
Infomat MATERIALS SCIENCE, MULTIDISCIPLINARY-
CiteScore
37.70
自引率
3.10%
发文量
111
审稿时长
8 weeks
期刊介绍: InfoMat, an interdisciplinary and open-access journal, caters to the growing scientific interest in novel materials with unique electrical, optical, and magnetic properties, focusing on their applications in the rapid advancement of information technology. The journal serves as a high-quality platform for researchers across diverse scientific areas to share their findings, critical opinions, and foster collaboration between the materials science and information technology communities.
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