Skeletal Muscle Fatigue State Evaluation with Ultrasound Image Entropy

2020 ◽  
Vol 42 (6) ◽  
pp. 235-244
Author(s):  
Pan Li ◽  
Xuebing Yang ◽  
Guanjun Yin ◽  
Jianzhong Guo

Muscle fatigue often occurs over a long period of exercise, and it can increase the risk of muscle injury. Evaluating the state of muscle fatigue can avoid unnecessary overtraining and injury of the muscle. Ultrasound imaging can non-invasively visualize muscle tissue in real-time. Image entropy is commonly used to characterize the texture of an image. In this study, we evaluated changes in the ultrasound image entropy (USIE) during the fatigue process. Twelve volunteers performed static sustained contractions of biceps brachii at four different intensities (20%, 30%, 40%, and 50% of maximal voluntary contraction torque). The ultrasound images and surface electromyography (sEMG) signals were acquired during exercise to fatigue. We found that (1) the root-mean-square of the sEMG signal increased, the USIE decreased significantly with time during the sustained contractions; (2) the maximum endurance time (MET) and the decline percentage of USIE were significantly different ( p < .05) among the four contraction intensities; (3) the decline slope of USIE of the same volunteer was basically the same at different contraction intensities. The USIE could be a new method for the evaluation of skeletal muscle fatigue state.

2020 ◽  
Vol 38 (12) ◽  
pp. 773-779
Author(s):  
Patrícia Gabrielli Vassão ◽  
Gabriel Sobrinho Baldini ◽  
Kamila Verlene S.G. Vieira ◽  
Ana Beatriz Balão ◽  
Carlos Eduardo Pinfildi ◽  
...  

2019 ◽  
Vol 27 (4) ◽  
pp. 253-259
Author(s):  
Beyza Akyüz ◽  
Pınar Arpınar Avşar ◽  
Murat Bilge ◽  
Gökhan Deliceoğlu ◽  
Feza Korkusuz

1986 ◽  
Vol 60 (4) ◽  
pp. 1179-1185 ◽  
Author(s):  
T. Moritani ◽  
M. Muro ◽  
A. Nagata

Twelve male subjects were tested to determine the effects of motor unit (MU) recruitment and firing frequency on the surface electromyogram (EMG) frequency power spectra during sustained maximal voluntary contraction (MVC) and 50% MVC of the biceps brachii muscle. Both the intramuscular MU spikes and surface EMG were recorded simultaneously and analyzed by means of a computer-aided intramuscular spike amplitude-frequency histogram and frequency power spectral analysis, respectively. Results indicated that both mean power frequency (MPF) and amplitude (rmsEMG) of the surface EMG fell significantly (P less than 0.001) together with a progressive reduction in MU spike amplitude and firing frequency during sustained MVC. During 50% MVC there was a significant decline in MPF (P less than 0.001), but this decline was accompanied by a significant increase in rmsEMG (P less than 0.001) and a progressive MU recruitment as evidenced by an increased number of MUs with relatively large spike amplitude. Our data suggest that the surface EMG amplitude could better represent the underlying MU activity during muscle fatigue and the frequency powers spectral shift may or may not reflect changes in MU recruitment and rate-coding patterns.


2018 ◽  
Vol 597 (2) ◽  
pp. 373-374
Author(s):  
Aurora D. Foster ◽  
Liam F. Fitzgerald ◽  
Miles F. Bartlett ◽  
Chad R. Straight

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 1036
Author(s):  
Fuyuan Liao ◽  
Xueyan Zhang ◽  
Chunmei Cao ◽  
Isabella Yu-Ju Hung ◽  
Yanni Chen ◽  
...  

This study aimed to investigate the degree of regularity of surface electromyography (sEMG) signals during muscle fatigue during dynamic contractions and muscle recovery after cupping therapy. To the best of our knowledge, this is the first study assessing both muscle fatigue and muscle recovery using a nonlinear method. Twelve healthy participants were recruited to perform biceps curls at 75% of the 10 repetitions maximum under four conditions: immediately and 24 h after cupping therapy (−300 mmHg pressure), as well as after sham control (no negative pressure). Cupping therapy or sham control was assigned to each participant according to a pre-determined counter-balanced order and applied to the participant’s biceps brachii for 5 min. The degree of regularity of the sEMG signal during the first, second, and last 10 repetitions (Reps) of biceps curls was quantified using a modified sample entropy (Ems) algorithm. When exercise was performed immediately or 24 h after sham control, Ems of the sEMG signal showed a significant decrease from the first to second 10 Reps; when exercise was performed immediately after cupping therapy, Ems also showed a significant decrease from the first to second 10 Reps but its relative change was significantly smaller compared to the condition of exercise immediately after sham control. When exercise was performed 24 h after cupping therapy, Ems did not show a significant decrease, while its relative change was significantly smaller compared to the condition of exercise 24 h after sham control. These results indicated that the degree of regularity of sEMG signals quantified by Ems is capable of assessing muscle fatigue and the effect of cupping therapy. Moreover, this measure seems to be more sensitive to muscle fatigue and could yield more consistent results compared to the traditional linear measures.


2018 ◽  
Vol 33 (6) ◽  
pp. 1197-1205 ◽  
Author(s):  
Renata Luri Toma ◽  
Murilo Xavier Oliveira ◽  
Ana Cláudia Muniz Renno ◽  
E-Liisa Laakso

2009 ◽  
Vol 37 (1) ◽  
pp. 2 ◽  
Author(s):  
Steven L. Lehman ◽  
Ladora V. Thompson

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