Sudirman, Rubita and Chee, A. K. and Daud, W. B. (2010) Modeling of EEG signal sound frequency characteristic using time frequency analysis. In: 4th Asia International Conference on Mathematical Modelling & Computer Simulation (AMS 2010), 26-28 Mei 2010, Kota Kinabalu, Sabah.
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Official URL: http://dx.doi.org/10.1109/AMS.2010.52
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:||Conference or Workshop Item (Paper)|
|Uncontrolled Keywords:||ECG signal, Fast Fourier Transform, artifact filtering, moving average filter, sound frequency|
|Subjects:||T Technology > TK Electrical engineering. Electronics Nuclear engineering|
|Deposited By:||Liza Porijo|
|Deposited On:||25 Sep 2012 02:11|
|Last Modified:||25 Sep 2012 02:11|
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