An automatic detection and localization of P300 sub-components using ICA

Min Jing, Saeid Sanei, Alexander Sumich

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Independent component analysis (ICA) has been applied for separation (BSS), detection and localization of P300 sub-components in this project. Event-related potential (ERP) is obtained from EEG data of the schizophrenia patients. The frequency analysis method is applied to extract P300 sub-components from the background EEG signal that contains noise and artefacts. By using JADE algorithm and correlation analysis, P300 sub-components (P3a/P3b) have been separated effectively. The components are then localized based on the correlations between the electrodes and the estimated source signals.
LanguageEnglish
Title of host publicationIEEE International Workshop on Biomedical Circuits and Systems 2004
DOIs
Publication statusPublished - 27 Jun 2005
Event IEEE International Workshop on Biomedical Circuits and Systems 2004 - , Singapore
Duration: 1 Dec 20043 Dec 2004

Conference

Conference IEEE International Workshop on Biomedical Circuits and Systems 2004
CountrySingapore
Period1/12/043/12/04

Fingerprint

Independent component analysis
Electroencephalography
Blind source separation
Bioelectric potentials
Electrodes

Cite this

Jing, M., Sanei, S., & Sumich, A. (2005). An automatic detection and localization of P300 sub-components using ICA. In IEEE International Workshop on Biomedical Circuits and Systems 2004 https://doi.org/10.1109/BIOCAS.2004.1454167
Jing, Min ; Sanei, Saeid ; Sumich, Alexander. / An automatic detection and localization of P300 sub-components using ICA. IEEE International Workshop on Biomedical Circuits and Systems 2004. 2005.
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abstract = "Independent component analysis (ICA) has been applied for separation (BSS), detection and localization of P300 sub-components in this project. Event-related potential (ERP) is obtained from EEG data of the schizophrenia patients. The frequency analysis method is applied to extract P300 sub-components from the background EEG signal that contains noise and artefacts. By using JADE algorithm and correlation analysis, P300 sub-components (P3a/P3b) have been separated effectively. The components are then localized based on the correlations between the electrodes and the estimated source signals.",
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Jing, M, Sanei, S & Sumich, A 2005, An automatic detection and localization of P300 sub-components using ICA. in IEEE International Workshop on Biomedical Circuits and Systems 2004. IEEE International Workshop on Biomedical Circuits and Systems 2004, Singapore, 1/12/04. https://doi.org/10.1109/BIOCAS.2004.1454167

An automatic detection and localization of P300 sub-components using ICA. / Jing, Min; Sanei, Saeid; Sumich, Alexander.

IEEE International Workshop on Biomedical Circuits and Systems 2004. 2005.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - Independent component analysis (ICA) has been applied for separation (BSS), detection and localization of P300 sub-components in this project. Event-related potential (ERP) is obtained from EEG data of the schizophrenia patients. The frequency analysis method is applied to extract P300 sub-components from the background EEG signal that contains noise and artefacts. By using JADE algorithm and correlation analysis, P300 sub-components (P3a/P3b) have been separated effectively. The components are then localized based on the correlations between the electrodes and the estimated source signals.

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M3 - Conference contribution

BT - IEEE International Workshop on Biomedical Circuits and Systems 2004

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Jing M, Sanei S, Sumich A. An automatic detection and localization of P300 sub-components using ICA. In IEEE International Workshop on Biomedical Circuits and Systems 2004. 2005 https://doi.org/10.1109/BIOCAS.2004.1454167