Development of electromyography signal analysis technique for musculoskeletal disorders

Nordin, Munir Nafis (2021) Development of electromyography signal analysis technique for musculoskeletal disorders. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Musculoskeletal disorders (MsD) are an injury that affects human body movement. One of the common MsD problems is back pain and slipped disc. Early detection of MsD can be detected using an electromyography (EMG) signal. The suggested method is being introduced because MsD detection using standard physical assessment is not reliable and accurate. For example, at Social Security Organization (SOCSO) rehabilitation centre, a health screening exam was performed on patients to evaluate MsD problem. The activity is completed manually by the patient and with the assistance of an instructor. This current method fails to identify which specific muscle is in the problem, so the patient cannot be declared as a MsD patient accurately and scientifically. This study proposes a signal processing approach to detect muscular disorder using signal analysis techniques. EMG can detect the electrical signal produced by the muscles and will be used to assess muscle health and establish whether the patient is at risk of acquiring a musculoskeletal condition or is already suffering from it. In addition, the test can evaluate muscle fatigue by performing some activities using the Functional Range of Motion (FROM) task. Shimmer devices and software collect the muscle data at a specific region: the biceps, erector spine and trapezius muscles, both left and right. The data collected based on the task given will be processed using the Matlab software. Two methods, Fast Fourier Transform (FFT) and spectrogram will apply in command of the Matlab. By doing so, the output result shown is the activity of the muscle health condition. Then, the respondent can be categorized into fit and fatigued muscle conditions.

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