文献类型：期刊文献

中文题名：面向地铁低头族的颈部疲劳sEMG-JASA评价模型

英文题名：An sEMG-JASA evaluation model for the neck fatigue of subway phubbers

作者：贾淼[1];杨钟亮[1];陈育苗[2]

机构：[1]东华大学机械工程学院,上海201620;[2]华东理工大学艺术设计与传媒学院,上海200237

年份：2020

卷号：15

期号：4

起止页码：705

中文期刊名：智能系统学报

外文期刊名：CAAI Transactions on Intelligent Systems

收录：CSTPCD;;北大核心:【北大核心2017】；CSCD:【CSCD2019_2020】；

基金：国家自然科学基金项目(51305077);中央高校基本科研专项基金项目(2232018D3-27);浙江省健康智能厨房系统集成重点实验室开放基金项目(2014E10014);2017东华大学研究生核心课程建设项目(201711);上海设计学IV类高峰学科资助项目(DC17013)。

语种：中文

中文关键词：肌肉疲劳;表面肌电;低头族;时域指标;频域指标;幅频联合分析;前导实验;评价模型

外文关键词：muscle fatigue;surface electromyography;phubber;time domain index;frequency domain index;amplitude-frequency joint analysis;leading experiment;evaluation model

摘要：随着社会的发展地铁低头族已经在地铁上随处可见,为研究地铁低头族颈部肌肉疲劳与低头时间的变化关系,本文基于幅频联合分析法提出颈部肌肉疲劳评价模型。实验中共招募10名参试人员分别采集其颈部肌肉的表面肌电信号,利用疲劳联合分析模型对不同时间段内颈部肌肉的疲劳程度做出比较。实验结果显示,斜方肌和头夹肌的通道中中位频率值处于下降趋势,而均方根值处于上升趋势,说明肌肉产生疲劳并随着低头使用手机时间的增加颈部肌肉疲劳程度逐渐增加。该实验验证了疲劳评价模型的有效性,模型可对乘客发出疲劳提醒,帮助乘客形成良好的行为习惯,为开发智能穿戴系统提供依据。
With the development of society,subway phubbers have been seen everywhere on the subway.To analyze the relationship between neck muscle fatigue and bowing time of subway phubbers,this study proposes a neck muscle fatigue evaluation model based on the amplitude–frequency joint analysis method.In the experiment,10 participants were recruited to collect the surface electromyogram signals of their neck muscles.The fatigue degree of their neck muscles in different time quanta was compared with the fatigue joint analysis model.Results showed that the median frequencies of the trapezius and scalp muscle exhibited a downward trend,whereas the root–mean–square values exhibited an upward trend,indicating that muscle fatigue was obvious.Moreover,the fatigue degree of the neck muscle gradually increased with the increase in bowing time of subway phubbers when using a mobile phone.The experiment validates the effectiveness of the fatigue evaluation model.The model can alert passengers to fatigue,help passengers form good mobile phone usage habits,and provide a basis for the development of an intelligent wear system.