Auditory Source Localization by Time Frequency Analysis and Classification of Electroencephalogram Signals

Article ID

6Y61B

Auditory Source Localization by Time Frequency Analysis and Classification of Electroencephalogram Signals

Vidya Manian
Vidya Manian University of Puerto Rico at Mayaguez
Cesar A. Aceros-Moreno
Cesar A. Aceros-Moreno
Domingo Rodriguez
Domingo Rodriguez
Juan Valera
Juan Valera
DOI

Abstract

The temporal lobe or auditory cortex in the brain is involved in processing auditory stimuli. The auditory data processing capability in the brain changes as a person ages. In this paper, we use the hrtf method to produce sound in different directions as auditory stimulus. Experiments are conducted with auditory stimulation of human subjects. Electroencephalogram (EEG) recording from the subjects are made during the exposure to the sound. A set of time frequency analysis operators consisting of the cyclic short time Fourier transform and the continuous wavelet transform is applied to the pre-processed EEG signal and a classifier is trained with time-frequency power from training data. The support vector machine classifier is then used for source localization of the sound. The paper also presents results with respect to neuronal regions involved in processing multi source sound information.

Auditory Source Localization by Time Frequency Analysis and Classification of Electroencephalogram Signals

The temporal lobe or auditory cortex in the brain is involved in processing auditory stimuli. The auditory data processing capability in the brain changes as a person ages. In this paper, we use the hrtf method to produce sound in different directions as auditory stimulus. Experiments are conducted with auditory stimulation of human subjects. Electroencephalogram (EEG) recording from the subjects are made during the exposure to the sound. A set of time frequency analysis operators consisting of the cyclic short time Fourier transform and the continuous wavelet transform is applied to the pre-processed EEG signal and a classifier is trained with time-frequency power from training data. The support vector machine classifier is then used for source localization of the sound. The paper also presents results with respect to neuronal regions involved in processing multi source sound information.

Vidya Manian
Vidya Manian University of Puerto Rico at Mayaguez
Cesar A. Aceros-Moreno
Cesar A. Aceros-Moreno
Domingo Rodriguez
Domingo Rodriguez
Juan Valera
Juan Valera

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Vidya Manian. 2019. “. Global Journal of Computer Science and Technology – G: Interdisciplinary GJCST-G Volume 19 (GJCST Volume 19 Issue G3): .

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Issue Cover
GJCST Volume 19 Issue G3
Pg. 13- 19
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GJCST-G Classification: C.3
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Auditory Source Localization by Time Frequency Analysis and Classification of Electroencephalogram Signals

Vidya Manian
Vidya Manian University of Puerto Rico at Mayaguez
Cesar A. Aceros-Moreno
Cesar A. Aceros-Moreno
Domingo Rodriguez
Domingo Rodriguez
Juan Valera
Juan Valera

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