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一种基于柔性多孔石墨烯压力传感器的低成本、便携式无线鞋内系统。

A Low-Cost, Portable, and Wireless In-Shoe System Based on a Flexible Porous Graphene Pressure Sensor.

作者信息

Cui Tianrui, Yang Le, Han Xiaolin, Xu Jiandong, Yang Yi, Ren Tianling

机构信息

School of Integrated Circuit, Tsinghua University, Beijing 100084, China.

Beijing National Research Center for Information Science and Technology (BNRist), Tsinghua University, Beijing 100084, China.

出版信息

Materials (Basel). 2021 Oct 28;14(21):6475. doi: 10.3390/ma14216475.

Abstract

Monitoring gait patterns in daily life will provide a lot of biological information related to human health. At present, common gait pressure analysis systems, such as pressure platforms and in-shoe systems, adopt rigid sensors and are wired and uncomfortable. In this paper, a biomimetic porous graphene-SBR (styrene-butadiene rubber) pressure sensor (PGSPS) with high flexibility, sensitivity (1.05 kPa), and a wide measuring range (0-150 kPa) is designed and integrated into an insole system to collect, process, transmit, and display plantar pressure data for gait analysis in real-time via a smartphone. The system consists of 16 PGSPSs that were used to analyze different gait signals, including walking, running, and jumping, to verify its daily application range. After comparing the test results with a high-precision digital multimeter, the system is proven to be more portable and suitable for daily use, and the accuracy of the waveform meets the judgment requirements. The system can play an important role in monitoring the safety of the elderly, which is very helpful in today's society with an increasingly aging population. Furthermore, an intelligent gait diagnosis algorithm can be added to realize a smart gait monitoring system.

摘要

监测日常生活中的步态模式将提供许多与人类健康相关的生物信息。目前,常见的步态压力分析系统,如压力平台和鞋内系统,采用刚性传感器,有线连接且穿着不舒适。本文设计了一种具有高柔韧性、灵敏度(1.05 kPa)和宽测量范围(0 - 150 kPa)的仿生多孔石墨烯 - 丁苯橡胶压力传感器(PGSPS),并将其集成到鞋垫系统中,以通过智能手机实时收集、处理、传输和显示足底压力数据用于步态分析。该系统由16个PGSPS组成,用于分析不同的步态信号,包括行走、跑步和跳跃,以验证其日常应用范围。将测试结果与高精度数字万用表进行比较后,证明该系统更便于携带且适合日常使用,波形精度满足判断要求。该系统在监测老年人安全方面可发挥重要作用,在当今人口老龄化日益严重的社会中非常有帮助。此外,可以添加智能步态诊断算法来实现智能步态监测系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/391e/8585424/e431f181ec5c/materials-14-06475-g001.jpg

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