Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis

Sudirman, Rubita and A. K. Chee and Wan Daud, Wan Mohd Bukhari (2010) Modeling Of EEG Signal Sound Frequency Characteristic Using Time Frequency Analysis. Mathematical/Analytical Modelling and Computer Simulation (AMS). pp. 221-226. ISSN 978-1-4244-7196-6

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Abstract

This paper presents the study of sound frequency characteristic based on Electroencephalography (EEG) signals. The study includes feature extraction of the EEG signals with respect to different sound frequencies, covering low frequency (40 Hz), mid-range frequency (5000 Hz), and high frequency (15000 Hz). Human brain activities are expected to be different when exposed to different sound frequencies, and can be shown through EEG signals. In this paper, EEG signal characterization is done using Fast Fourier Transform (FFT), moving average filters, and simple artefact filtering with reference EEG data per individual. Based on the characteristics of the EEG signal, the sound frequency can be categorized and identified using the proposed method.

Item Type:	Article
Uncontrolled Keywords:	ECG signal, sound frequency, artifact filtering, Fast Fourier Transform (FFT), moving average filter
Divisions:	Faculty of Electrical Engineering > Department of Control, Instrumentation & Automation
Depositing User:	Mr. Wan Mohd Bukhari Wan Daud
Date Deposited:	19 Sep 2012 07:38
Last Modified:	06 Jan 2022 12:50
URI:	http://eprints.utem.edu.my/id/eprint/4534
Statistic Details:	View Download Statistic

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