Muscle Fatigue Detections During Arm Movement using EMG Signal
Muscle Fatigue Detections During Arm Movement using EMG Signal
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DOI：
10.1088/1757-899x/557/1/012004
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发表时间：
2019-06
期刊：
影响因子：
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通讯作者：
B. N. Cahyadi;W. Khairunizam;I. Zunaidi;L.H. Ling;A. Shahriman;M. Zuradzman;W. Mustafa;N. Noriman
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文献类型：
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作者：
B. N. Cahyadi;W. Khairunizam;I. Zunaidi;L.H. Ling;A. Shahriman;M. Zuradzman;W. Mustafa;N. Noriman
肌电图是通过分析肌肉和肌肉收缩期间发出的电信号来研究肌肉功能的方法。在脑卒中后的康复过程中，肌肉活动的监测对于了解肌肉力量的发展是非常重要的。肌电信号是由肌肉活动产生的信号，包含肌肉收缩、肌力和肌无力等信息。需要长时间的康复过程会导致肌肉疲劳，康复变得低效。本研究的目的是利用肌电信号分析手臂运动过程中的肌肉疲劳。本研究利用肌电信号对三角肌和肱二头肌进行监测，并利用MATLAB对信号进行分析。选择5名健康受试者进行康复实验。在数据收集中使用功能和基本运动。提出了将均值作为频域特征用于分析的方法。结果表明，三角肌和肱二头肌的收缩信号随时间的推移不断减弱。脑卒中患者在康复过程中，不宜长时间进行运动。
Electromyography is a study of muscle function through the analysis of electrical signals emanated during muscular and muscle contractions. In the post-stroke rehabilitation process, monitoring of muscle activity is very important to know the developments of muscle strength. EMG signals, which produced by muscle activity have information such as muscle contractions, muscle strength and muscle weakness. Rehabilitation process that takes a long period of time can cause muscle fatigue, and the rehabilitation becomes inefficient. The objective of this research is to analyze the muscle fatigue during arm movements by using EMG signals. In this study, deltoid and biceps are monitored by using EMG and the signal are analyzed by using MATLAB. Five healthy subjects are selected to perform the rehabilitation in the experiments. Functional and fundamental movements are used in the data collections. The mean as a feature from a frequency domain is proposed to be used in the analysis. The results show that the signal contractions from deltoid and biceps muscles decreased constantly by the time. In the process of rehabilitation, the stroke sufferers should not do the exercise in a long period of time.