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Lossless measurement and evaluation for predicting the rating of perceived physical fatigue

机译:无损测量和评估,可预测感觉到的疲劳程度

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There is a muscle force failure caused by physical fatigue. Since the change in myoelectrical activity occurs in advance of the failure, surface EMG (SEMG) is valuable. However, the accuracy of SEMG manifestation is not always guaranteed spatiotemporally. We first introduced a 2D surface electrode to search the location of electrode on the skin where SEMG manifestations are fully detected with high accuracy. Furthermore, enough precision is important to interpret the physiological activities. Then we determine the motion related target muscles, adopting the idea of muscle synergy. That is, based on the fact that functional activities are stemmed from a hierarchical multi-timescale system, we model a rating of perceived physical fatigue (RPF) integrating the psychological manifestation (long-term event) by physiological one (short-term event). This will lead to lossless measurement and evaluation for a faster prediction of the physical fatigue induced failure. The ultimate goal is a ubiquitous strategy for risk avoidance by establishing the RPF for safely controlling the electrical power assist.
机译:身体疲劳会导致肌肉力量衰竭。由于肌电活动的变化是在故障发生之前发生的,因此表面肌电图(SEMG)很有用。但是,不一定总是在时空上保证SEMG表现的准确性。我们首先引入了2D表面电极,以搜索电极在皮肤上的位置,在此位置上可以高精度地完全检测到SEMG表现。此外,足够的精度对于解释生理活动很重要。然后,我们采用肌肉协同作用的思想来确定与运动相关的目标肌肉。也就是说,基于功能活动源于分层的多时间尺度系统这一事实,我们建立了将生理表现(长期事件)与生理表现(短期事件)相结合的感知身体疲劳(RPF)的评分模型。这将导致无损测量和评估,从而更快地预测物理疲劳引起的故障。最终目标是通过建立可安全控制电力辅助的RPF来规避风险的普遍策略。

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