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基于计算机平均肌电图轮廓的病理性步态诊断

Pathologic gait diagnosis with computer-averaged electromyographic profiles.

作者信息

Winter D A

出版信息

Arch Phys Med Rehabil. 1984 Jul;65(7):393-8.

PMID:6742998
Abstract

A computer-assisted approach is described which compares EMG profiles from each patient's gait with similar profiles from able-bodied subjects. The EMG and footswitch signals from walking trials were telemetered via a six-channel biotelemetry system; the EMGs were further processed to obtain a linear envelope before A/D conversion into a desktop computer. Simultaneously, a video camera recorded the patient's walking pattern. From 32sec of converted data, a number of strides were selected for averaging to achieve a mean ensemble pattern over the stride period, which is set to 100% for each selected stride. The ensemble average of each muscle's EMG was superimposed on a plot of the EMG patterns from able-bodied subjects. The diagnostician then correlated atypical patterns from each muscle with the stopped or slow motion television image of each patient's gait. Positive corroborative evidence yields detailed diagnostic statements about the cause of their abnormal gait. Such evidence is valuable in planning future rehabilitative procedures or in assessing the results of past efforts.

摘要

本文描述了一种计算机辅助方法,该方法将每位患者步态的肌电图(EMG)轮廓与健全受试者的类似轮廓进行比较。步行试验中的肌电图和脚踏开关信号通过六通道生物遥测系统进行遥测;在将肌电图进行A/D转换到台式计算机之前,对其进行进一步处理以获得线性包络。同时,用摄像机记录患者的行走模式。从32秒的转换数据中,选择若干步幅进行平均,以获得步幅周期内的平均总体模式,每个选定步幅的该模式设定为100%。将每块肌肉肌电图的总体平均值叠加在健全受试者肌电图模式的图表上。然后,诊断医生将每块肌肉的异常模式与每位患者步态的定格或慢动作电视图像相关联。阳性确证证据会产生关于其异常步态原因的详细诊断陈述。这些证据对于规划未来的康复程序或评估过去努力的结果很有价值。

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