Research Article | OPEN ACCESS
Classification of EMG Signal Based on Human Percentile using SOM
M.H. Jali, Z.H. Bohari, M.F. Sulaima, M.N.M. Nasir and H.I. Jaafar
Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Hang Tuah Jaya,
76100 Durian Tunggal, Melaka, Malaysia
Research Journal of Applied Sciences, Engineering and Technology 2014 2:235-242
Received: April 08, 2014 | Accepted: April 28, 2014 | Published: July 10, 2014
Abstract
Electromyography (EMG) is a bio signal that is formed by physiological variations in the state of muscle fibre membranes. Pattern recognition is one of the fields in the bio-signal processing which classified the signal into certain desired categories with subject to their area of application. This study described the classification of the EMG signal based on human body percentile using Self Organizing Mapping (SOM) technique. Different human percentile definitively varies the arm circumference size. Variation of arm circumference is due to fatty tissue that lay between active muscle and skin. Generally the fatty tissue would decrease the overall amplitude of the EMG signal. Data collection is conducted randomly with fifteen subjects that have numerous percentiles using non-invasive technique at Biceps Brachii muscle. The signals are then going through filtering process to prepare them for the next stage. Then, five well known time domain feature extraction methods are applied to the signal before the classification process. Self Organizing Map (SOM) technique is used as a classifier to discriminate between the human percentiles. Result shows that SOM is capable in clustering the EMG signal to the desired human percentile categories by optimizing the neurons of the technique.
Keywords:
Biceps brachii, classification, electromyography, human percentile, pattern recognition, self organizing map,
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Competing interests
The authors have no competing interests.
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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
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The authors have no competing interests.
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