利用可穿戴传感器采集的数据分析肌肉疲劳对步态特征的影响

Aishwarya Balakrishnan, Jeevan Medikonda, Pramod K. Namboothiri
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引用次数: 4

摘要

帕金森氏症(PD)患者遭受许多与步态相关的障碍。多种因素导致步态模式的改变,其中肌肉疲劳起着重要作用。传统的步态分析技术涉及昂贵的实验室设备,需要专门的人员或软件工具进行分析。本文提出了一种嵌入可穿戴传感器网络的便携式无线数据采集系统,可以在无约束环境下实时采集步态信号。已经进行了实验来证明所提出系统的有效性,并使用肌力图技术检查肌肉疲劳在步态监测中的影响。结果显示,受肌肉疲劳的影响,平均步幅时间和节奏有明显的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of the effect of muscle fatigue on gait characteristics using data acquired by wearable sensors
Parkinson's disease (PD) patients suffer from numerous gait-related disturbances. Various factors contribute to the alteration in gait patterns, among which muscle fatigue plays a significant role. Traditional gait analysis techniques involve laboratory types of equipment that are expensive and require specialized personnel or software tools for analysis. In this paper, a portable wireless data acquisition system embedded with a network of wearable sensors is proposed that can aid real-time gait signal acquisition in an unconstrained environment. Experiments have been carried out to demonstrate the effectiveness of the proposed system and to examine the effect of muscle fatigue in gait monitoring using mechanomyography techniques. Results show distinct variability in mean stride time and cadence with the influence of muscle fatigue.
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