【摘要】：肌肉疲勞是一種復(fù)雜的生理現(xiàn)象。針對(duì)利用表面肌電信號(hào)實(shí)時(shí)評(píng)估肌肉疲勞,要求疲勞指標(biāo)兼具快速、可靠、抗噪的問(wèn)題,提出基于邊際譜熵的肌肉疲勞實(shí)時(shí)評(píng)估方法。首先,利用不同數(shù)據(jù)長(zhǎng)度的確定性周期信號(hào)和高斯白噪聲分析了邊際譜熵快速性與數(shù)據(jù)長(zhǎng)度穩(wěn)健性;其次,利用10名受試者握力持續(xù)靜態(tài)收縮狀態(tài)下從100%MVC下降到50%MVC時(shí)橈側(cè)腕長(zhǎng)伸肌的肌肉疲勞信號(hào),分析了邊際譜熵評(píng)估肌肉疲勞的可靠性與應(yīng)用于不同個(gè)體的穩(wěn)定性;最后,在某一受試者肌肉疲勞信號(hào)中加入高斯白噪聲和心電噪聲考察了邊際譜熵的抗噪性。實(shí)驗(yàn)結(jié)果表明,邊際譜熵與近似熵和中值頻率相比計(jì)算快速,數(shù)據(jù)長(zhǎng)度穩(wěn)健性更優(yōu);線性擬合優(yōu)度較佳(0.46±0.14),能可靠地評(píng)估肌肉疲勞;斜率變異系數(shù)較低(30.30%),對(duì)不同個(gè)體穩(wěn)定性高;加入高斯白噪聲和心電噪聲后邊際譜熵?cái)M合優(yōu)度變化率較低(分別為34.39%和3.78%),具有良好的抗噪性。因此邊際譜熵兼具快速、能可靠評(píng)估肌肉疲勞以及抗噪等優(yōu)點(diǎn),為實(shí)時(shí)評(píng)估肌肉疲勞提供一種新方法。
[Abstract]:Muscle fatigue is a complex physiological phenomenon. Aiming at the problem of real-time evaluation of muscle fatigue by surface electromyography (EMG) signals, which requires both fast, reliable and anti-noise indexes, a real-time evaluation method of muscle fatigue based on marginal spectrum entropy is proposed. Firstly, using deterministic periodic signals with different data lengths and Gao Si white noise, the paper analyzes the marginal spectral entropy rapidity and data length robustness. Using the muscle fatigue signal of extensor Carpi radialis longus under the condition of continuous static contraction of grip force from 100%MVC to 50%MVC, the marginal spectrum entropy was analyzed to evaluate the reliability of muscle fatigue and the stability of muscle applied to different individuals. The noise resistance of marginal spectral entropy was investigated by adding Gao Si white noise and electrocardiogram noise to the muscle fatigue signal. The experimental results show that the marginal spectral entropy is faster than the approximate entropy and the median frequency, the data length is more robust, the linear fit is better (0.46 鹵0.14), the slope coefficient of variation is lower (30.30%), and the slope coefficient of variation is higher for different individuals. When Gao Si white noise and ECG noise were added, the variation rate of marginal spectral entropy goodness of fit was lower (34.39% and 3.78%, respectively), and had good noise resistance. Therefore, the marginal spectral entropy has the advantages of fast, reliable evaluation of muscle fatigue and anti-noise, which provides a new method for real-time evaluation of muscle fatigue.
【作者單位】： 合肥工業(yè)大學(xué)智能制造技術(shù)研究院;合肥工業(yè)大學(xué)機(jī)械工程學(xué)院;
【基金】：科技型中小企業(yè)技術(shù)創(chuàng)新基金(11C26213402042)項(xiàng)目資助
【分類(lèi)號(hào)】：R318;TN911.7

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