肌电图
肌肉疲劳
信号(编程语言)
时域
频域
噪音(视频)
物理医学与康复
计算机科学
康复
医学
人工智能
物理疗法
计算机视觉
图像(数学)
程序设计语言
作者
Moehammad Dzaky Fauzan Ma'as,Masitoh,Ahmad Zahi Ulul Azmi,Suprijanto Suprijanto
标识
DOI:10.1109/ica.2017.8068428
摘要
Muscle fatigue is one of the important parameters that must be known during physiotherapy. Undetected muscle fatigue for a long time can cause injury to the subject. This paper presents method and algorithm to determine fatigue of muscle during doing some exercise which can be used for real-time monitoring post-stroke rehabilitation patient by using Electromyography (EMG). In general, EMG signal is commonly used for recording muscle activity. Extracted features are purposed to minimize the loss of useful information embedded in the signal with noise. EMG signal has better performance in frequency domain than in time domain. Median Frequency (MDF) is one of the standard parameter to indicate fatigue. Using the proposed method and algorithm, some experimental test show shows that MDF decreases 1 to 3 Hz and the slope of MDF sticks to certain value below zero.
科研通智能强力驱动
Strongly Powered by AbleSci AI