Assessment of muscle fatigue using sonomyography: Muscle thickness change detected from ultrasound images

等长运动 肌肉疲劳 肌电图 超声波 肱二头肌 收缩(语法) 生物医学工程 肌肉收缩 解剖 医学 材料科学 物理医学与康复 内科学 放射科
作者
Jianrong Shi,Yong‐Ping Zheng,Xiao Chen,Q.H. Huang
出处
期刊:Medical Engineering & Physics [Elsevier BV]
卷期号:29 (4): 472-479 被引量:151
标识
DOI:10.1016/j.medengphy.2006.07.004
摘要

Muscle fatigue is an exercise-induced reduction in maximal voluntary muscle force. As the surface electromyography (SEMG) can be used to estimate the features of neuromuscular activations associated with muscle contractions, it has been widely employed as an objective tool to evaluate muscle fatigue. On the other hand, ultrasound imaging can inherently provide the morphological information of individual muscle, thus the architectural changes of muscles during fatigue can be obtained. In this study, we demonstrated the feasibility of using the dimensional change of muscles detected by ultrasound images, named as sonomyography (SMG), to characterize the behavior of muscles when they were in fatigue. The SEMG signals of the muscles were also recorded simultaneously and used for comparison. The right biceps brachii muscles of 8 normal young male adult subjects were tested for 30 s under 80% of the maximal voluntary isometric contraction. The muscle fatigue was indicated by the change of the root-mean-square (RMS) and median frequency (MDF) of the SEMG signals. The results showed that the SEMG RMS had a linear increase with time with a rate of 2.9 ± 1.9 %/s (mean ± S.D.), while the MDF decreased linearly with a rate of −0.60 ± 0.26 Hz/s. The muscle thickness, detected from the ultrasound images, continuously increased during the muscle fatigue but with a nonlinear increase with time, which was rapid during the initial 8.1 ± 2.1 s with a mean deformation rate of 0.30 ± 0.19 %/s and then became slower with a rate of 0.067 ± 0.024 %/s up to 20 s after the contraction. The muscle deformation at 20 s was 3.5 ± 1.6%. The results demonstrated that the architectural change of muscles detected using SMG could potentially provide complementary information for SEMG for the muscle fatigue assessment.
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