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首页> 外文期刊>Journal of medical engineering & technology >Strategies to identify changes in SEMG due to muscle fatigue during cycling.
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Strategies to identify changes in SEMG due to muscle fatigue during cycling.

机译:识别由于骑车期间肌肉疲劳而导致SEMG变化的策略。

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摘要

Detection, quantification and analysis of muscle fatigue are crucial in occupational/rehabilitation and sporting settings. Sports organizations such as the Australian Institute of Sports (AIS) currently monitor fatigue by a battery of tests including invasive techniques that require taking blood samples and/or muscle biopsies, the latter of which is highly invasive, painful, time consuming and expensive. SEMG is non-invasive monitoring of muscle activation and is an indication of localized muscle fatigue based on the observed shift of the power spectral density of the SEMG. But the success of SEMG based techniques is currently limited to isometric contraction and is not acceptable to the human movement community. This paper proposes and tests the use of spectral analysis of narrow windows of SEMG near the peak of a cyclic activity to identify the onset of muscle fatigue during cyclic activities. The results demonstrate a highly significant relationship of reduction of the median frequency with the onset of muscle fatigue. The paper also reports the validation of the SEMG study using biochemical analysis of muscle biopsy and blood tests and further verified using power output of the cycle and speed of pedalling.
机译:对肌肉疲劳的检测,量化和分析对于职业/康复和运动环境至关重要。诸如澳大利亚体育学院(AIS)之类的体育组织目前正在通过一系列测试来监测疲劳,这些测试包括需要抽取血液样本和/或肌肉活检的侵入性技术,而后者需要高度侵入性,痛苦,费时且昂贵。 SEMG是对肌肉激活的无创监测,是基于观察到的SEMG功率谱密度变化而显示的局部肌肉疲劳的指标。但是,基于SEMG的技术的成功目前仅限于等距收缩,这是人类运动界无法接受的。本文提出并测试了在循环活动峰值附近的SEMG窄窗口光谱分析的用途,以识别循环活动期间肌肉疲劳的发作。结果表明,中位数频率的降低与肌肉疲劳发作的高度相关。该论文还报告了SEMG研究的验证,该研究使用了肌肉活检和血液测试的生化分析,并通过脚踏车的循环功率输出和脚蹬速度进行了进一步验证。

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