Open AccessMuscle Fatigue Detections During Arm Movement using EMG Signal
Author(s) -
Basri Noor Cahyadi,
Wan Khairunizam,
I. Zunaidi,
Lee Hui Ling,
A. B. Shahriman,
Zuradzman Mohamad Razlan,
Wan Azani Mustafa,
N. Z. Noriman
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/557/1/012004
Subject(s) - biceps , physical medicine and rehabilitation , electromyography , deltoid muscle , muscle fatigue , rehabilitation , deltoid curve , medicine , muscle weakness , signal (programming language) , biceps brachii muscle , physical therapy , computer science , anatomy , programming language
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.