Tengku Zawawi , Tengku Nor Shuhada and Abdullah, Abdul Rahim and Shair, Ezreen Farina and Isa, Halim (2013) Electromygraphy Signal Analysis Using Spectrogram. In: 2013 IEEE Student Conference on Research and Development (SCOReD), 16-17 December 2013, Putrajaya, Malaysia.
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Abstract
Electromyography (EMG) is known as complex bioelectricity signals that representing the contraction of the muscle in humanbody. The EMG signal offers useful information that can help to understand the human movement. Many techniques have been proposed by various researchers such as fast Fourier transforms (FFT). However, the technique only gives temporal information of the signal and does not suitable for EMG that consists of magnitude and frequency variation. In this paper,the analysis of EMG signal is presented using time-frequency distribution (TFD) which is spectrogram with different window size. Since the spectrogram represent the theEMG signal in time-frequency representation (TFR), it is very appropriate to analyze the signal. The EMG signals from Biceps muscle of two subjects are collected for body position of 0° and 90°. From the TFR, parameters of the signal such as instantaneous fundamental root mean square (RMS) voltage (Vrms) are estimated. To identify the suitable windows size, spectrogram with size window of 64, 256, 512 and 1024 is used to analyze the signal and the performance of the TFR are evaluated. The results show that spectrogram with window size of 512 gives optimal TFR of the EMG signals and suitable to characterize the signal.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Faculty of Electrical Engineering > Department of Control, Instrumentation & Automation |
| Depositing User: | Ezreen Farina Shair |
| Date Deposited: | 07 Feb 2014 03:29 |
| Last Modified: | 28 May 2015 04:14 |
| URI: | http://eprints.utem.edu.my/id/eprint/11032 |
| Statistic Details: | View Download Statistic |
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