This study is aimed at assessing muscle fatigue during a static contraction using multifractal analysis and found that the surface electromyographic （SEMG） signals characterized multiffactality during a static contr...This study is aimed at assessing muscle fatigue during a static contraction using multifractal analysis and found that the surface electromyographic （SEMG） signals characterized multiffactality during a static contraction. By applying the method of direct determination ofthef（a） singularity spectrum, the area of the multifractal spectrum of the SEMG signals was computed. The results showed that the spectrum area significantly increased during muscle fatigue. Therefore the area could be used as an assessor of muscle fatigue. Compared with the median frequency （MDF）--the most popular indicator of muscle fatigue, the spectrum area presented here showed higher sensitivity during a static contraction. So the singularity spectrum area is considered to be a more effective indicator than the MDF for estimating muscle fatigue.展开更多
An improved approximate entropy (ApEn) is presented and applied to characterize surface electromyography (sEMG) signals. In most previous experiments using nonlinear dynamic analysis, this certain processing was often...An improved approximate entropy (ApEn) is presented and applied to characterize surface electromyography (sEMG) signals. In most previous experiments using nonlinear dynamic analysis, this certain processing was often confronted with the problem of insufficient data points and noisy circumstances, which led to unsatisfactory results. Compared with fractal dimension as well as the standard ApEn, the improved ApEn can extract information underlying sEMG signals more efficiently and accu- rately. The method introduced here can also be applied to other medium-sized and noisy physiological signals.展开更多
The sEMG signals are collected from the vastus lateralis,vastus medialis,biceps femoris,and semitendinosus of lower extremity during level walking among control subjects and knee osteoarthritis (OA) patients,the latte...The sEMG signals are collected from the vastus lateralis,vastus medialis,biceps femoris,and semitendinosus of lower extremity during level walking among control subjects and knee osteoarthritis (OA) patients,the latter including mild,moderate and severe degree.The 5-fold cross-validation is used to measure the accuracy of the proposed analysis algorithm on collected sEMG recordings.For comparison,the more classical feature vectors of form factor,degree of skewness,kurtosis,and wavelet entropy are also tested.In experiment,the normalized energy ratio and marginal spectrum ratio achieve larger accuracy than the other features for all the four muscular groups.Moreover the accuracy of vastus medialis and biceps femoris are larger than that of vastus lateralis and semitendinosus.These results suggest that the normalized energy ratio and marginal spectrum ratio via the analysis of knee sEMG signals by HHT can server as characteristic parameters to easily classify osteoarthritis with noninvasive method.The more important muscular groups for maintaining the knee joint function are medialis and biceps femoris;as a result of that they should be exercise especially for rehabilitation.展开更多
基金Project (No. 2005CB724303) supported by the National Basic Re-search Program (973) of China
文摘This study is aimed at assessing muscle fatigue during a static contraction using multifractal analysis and found that the surface electromyographic （SEMG） signals characterized multiffactality during a static contraction. By applying the method of direct determination ofthef（a） singularity spectrum, the area of the multifractal spectrum of the SEMG signals was computed. The results showed that the spectrum area significantly increased during muscle fatigue. Therefore the area could be used as an assessor of muscle fatigue. Compared with the median frequency （MDF）--the most popular indicator of muscle fatigue, the spectrum area presented here showed higher sensitivity during a static contraction. So the singularity spectrum area is considered to be a more effective indicator than the MDF for estimating muscle fatigue.
基金Project supported by the National Natural Science Foundation of China (No. 60171006) and the National Basic Research Program (973) of China (No. 2005CB724303)
文摘An improved approximate entropy (ApEn) is presented and applied to characterize surface electromyography (sEMG) signals. In most previous experiments using nonlinear dynamic analysis, this certain processing was often confronted with the problem of insufficient data points and noisy circumstances, which led to unsatisfactory results. Compared with fractal dimension as well as the standard ApEn, the improved ApEn can extract information underlying sEMG signals more efficiently and accu- rately. The method introduced here can also be applied to other medium-sized and noisy physiological signals.
基金Sponsored by the International Science and Technology Cooperation Project of China(Grant No.2009DFA32050)
文摘The sEMG signals are collected from the vastus lateralis,vastus medialis,biceps femoris,and semitendinosus of lower extremity during level walking among control subjects and knee osteoarthritis (OA) patients,the latter including mild,moderate and severe degree.The 5-fold cross-validation is used to measure the accuracy of the proposed analysis algorithm on collected sEMG recordings.For comparison,the more classical feature vectors of form factor,degree of skewness,kurtosis,and wavelet entropy are also tested.In experiment,the normalized energy ratio and marginal spectrum ratio achieve larger accuracy than the other features for all the four muscular groups.Moreover the accuracy of vastus medialis and biceps femoris are larger than that of vastus lateralis and semitendinosus.These results suggest that the normalized energy ratio and marginal spectrum ratio via the analysis of knee sEMG signals by HHT can server as characteristic parameters to easily classify osteoarthritis with noninvasive method.The more important muscular groups for maintaining the knee joint function are medialis and biceps femoris;as a result of that they should be exercise especially for rehabilitation.
