肌电图
工作(物理)
计算机科学
相关性(法律)
领域(数学)
扭矩
物理医学与康复
人为因素与人体工程学
接头(建筑物)
毒物控制
医学
工程类
数学
机械工程
结构工程
物理
环境卫生
政治学
纯数学
法学
热力学
作者
Göran M Hägg,Alwin Luttmann,Matthias Jäger
标识
DOI:10.1016/s1050-6411(00)00022-5
摘要
Surface electromyography (SEMG) is an important tool for work load assessment in ergonomics. Several different approaches using amplitude as well as frequency parameters give fruitful information depending on question at issue in the laboratory as well as in field studies. One basic factor determining the choice of analysis method is whether the SEMG is interpreted as an indicator of forces/torques or pure muscular activation. Two methods for occupational SEMG data reduction representing two different approaches to SEMG applications in ergonomics, Exposure Variation Analysis (EVA), and Joint Analysis of EMG Spectrum and Amplitude (JASA), applied on the same SEMG recording from three muscles during urology surgeon work, have been compared. The EVA method categorised the three muscle recordings as too static with no EMG gaps while the JASA method identifies fatigue in two of the three recordings. The practical relevance of these findings is discussed.
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