Electromyography Signal Analysis Using Time and Frequency Domain for Health Screening System Task

T.N.S. Tengku Zawawi, A.R. Abdullah, W.T. Jin, R. Sudirman, N.M. Saad

Abstract


Musculoskeletal disorder (MSDs) is
one of the most popular issues of occupational
injuries and disabilities. It has a big impact and
creates a big problem for industries to be resolved.
In MSDs, electromyography (EMG) is one of the
methods to be studied in order to detect MSDs
problem. This research focuses on the EMG signal
analysis by using time domain and frequency
domain (Welch Power Spectral Density) method.
It gives more information from the signal and it
is the most suitable method for classifying the
moments in order to identify the behavioural
of the signals. Axial rotational reach and upper
level reach task from Health Screening Program
(HST) is performed using functional range of
motion (FROM) by considering left and right
biceps brachii muscles to be analysed. There are
two parameters chosen for each time and for each
frequency domain to be tested, which are mean
an absolute value (MAV) and root mean square
(RMS) for time domain. Median frequency (MDF)
and mean frequency (MNF) are for frequency
domain. The results showed that frequency
domain analysis is able to give more parameter
and information of the signal. Upper level reach
acquires more effort to perform the task compared
to axial rotational reach for left and right biceps
brachii. However, different performances of
the signal obtained in classifying the moments
from t-test analysis due to p-value. The best
performance to classify signal characteristics is the
lowest p-value which is 7.369E-05 (MAV), 6.9504E-
05 (RMS), 0.0054 (MDF). However, p-value for
0.0515 is rejected because it is greater than 0.05.
It is concluded that the frequency domain is able
to give more information of the signal, however
for classifications moments, time domain is better
compared to the higher accuracy result. This study
is very important to give the idea in the future
analysis of EMG signal in the aspect of detecting
MSDs in human body in health screening task.


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