Musculoskeletal disorder (MSDs) isone of the most popular issues of occupationalinjuries and disabilities. It has a big impact andcreates a big problem for industries to be resolved.In MSDs, electromyography (EMG) is one of themethods to be studied in order to detect MSDsproblem. This research focuses on the EMG signalanalysis by using time domain and frequencydomain (Welch Power Spectral Density) method.It gives more information from the signal and itis the most suitable method for classifying themoments in order to identify the behaviouralof the signals. Axial rotational reach and upperlevel reach task from Health Screening Program(HST) is performed using functional range ofmotion (FROM) by considering left and rightbiceps brachii muscles to be analysed. There aretwo parameters chosen for each time and for eachfrequency domain to be tested, which are meanan absolute value (MAV) and root mean square(RMS) for time domain. Median frequency (MDF)and mean frequency (MNF) are for frequencydomain. The results showed that frequencydomain analysis is able to give more parameterand information of the signal. Upper level reachacquires more effort to perform the task comparedto axial rotational reach for left and right bicepsbrachii. However, different performances ofthe signal obtained in classifying the momentsfrom t-test analysis due to p-value. The bestperformance to classify signal characteristics is thelowest p-value which is 7.369E-05 (MAV), 6.9504E-05 (RMS), 0.0054 (MDF). However, p-value for0.0515 is rejected because it is greater than 0.05.It is concluded that the frequency domain is ableto give more information of the signal, howeverfor classifications moments, time domain is bettercompared to the higher accuracy result. This studyis very important to give the idea in the futureanalysis of EMG signal in the aspect of detectingMSDs in human body in health screening task
