Skeletal Muscle Fatigue State Evaluation with Ultrasound Image Entropy.


: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.


Ultrason Imaging


Ultrasonic imaging


Li P,Yang X,Yin G,Guo J




Has Abstract


2020-11-01 00:00:00












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    journal_title:Ultrasonic imaging

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    authors: He P

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    authors: Chen T,Chen TP,Tsai LM

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    journal_title:Ultrasonic imaging

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    authors: Jensen JA,Mathorne J,Gravesen T,Stage B

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    journal_title:Ultrasonic imaging

    pub_type: 杂志文章


    authors: Wen H

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    journal_title:Ultrasonic imaging

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    authors: Shen CC,Yang YC,Chen WS

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    journal_title:Ultrasonic imaging

    pub_type: 杂志文章


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    journal_title:Ultrasonic imaging

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    authors: Nordberg EP,Hall TJ

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    journal_title:Ultrasonic imaging

    pub_type: 杂志文章


    authors: Li PC,Shen CC

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    pub_type: 杂志文章,评审


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    authors: Nightingale K,Bentley R,Trahey G

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    pub_type: 杂志文章


    authors: Techavipoo U,Varghese T,Zagzebski JA,Stiles T,Frank G

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    pub_type: 杂志文章


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    authors: Knipp BS,Zagzebski JA,Wilson TA,Dong F,Madsen EL

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    pub_type: 杂志文章


    authors: Chiu LY,Chen A

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    authors: Geist RE,DuBois CH,Nichols TC,Caughey MC,Merricks EP,Raymer R,Gallippi CM

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