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-  2018 

基于表面肌电信号的颈部肌肉疲劳评价算法比较研究

DOI: doi:10.7507/1001-5515.201706014

Keywords: 颈部肌肉疲劳评价, 模糊近似熵, 谱矩比, 离散小波变换, 人因工程

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Abstract:

本研究旨在客观比较颈部肌肉疲劳评价算法的差异性,找出更加有效的颈部肌肉疲劳评价算法,为伏案姿势下颈部肌肉疲劳提供人因工程定量评价方法。本文利用无线生理仪采集了 15 名受试者使用记忆枕伏案 12 min 的颈部胸锁乳突肌的表面肌电信号,使用平均功率频率、谱矩比、离散小波变换、模糊近似熵以及复杂度 5 个算法计算出相应的肌肉疲劳指标;并使用最小二乘法对肌肉疲劳指标进行线性回归得出确定系数 R2 与斜率 k;确定系数 R2 可评价各种算法的抗干扰性;对斜率 k 进行柯尔莫哥洛夫—斯米洛夫检验得到最大垂直距离 Lmax,Lmax 可评价各种算法对疲劳程度的区分能力。统计结果表明,在抗干扰方面,模糊近似熵在不同高度的记忆枕下都具有最大的 R2,且模糊近似熵与平均功率频率、离散小波变换的差异具有统计学意义(P < 0.05);在区分疲劳程度方面,模糊近似熵仍具有最大的 Lmax,最大值达 0.496 7。本文研究结果表明,模糊近似熵无论是在抗干扰性还是疲劳程度的区分能力上都优于其他算法,因此在进行颈部肌肉疲劳评价时,我们建议可将模糊近似熵作为一个较好的评价指标

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