Separation and Localisation of P300 Sources and their Subcomponents Using Constrained Blind Source Separation

Loukianos Spyrou, Min Jing, Saeid Sanei, Alex Sumich

Research output: Contribution to journalArticle

Abstract

Separation and localisation of P300 sources and their constituent subcomponents for both visual and audio stimulations is investigated in this paper. An effective constrained blind source separation (CBSS) algorithm is developed for this purpose. The algorithm is an extension of the Infomax BSS system for which a measure of distance between a carefully measured P300 and the estimated sources is used as a constraint. During separation, the proposed CBSS method attempts to extract the corresponding P300 signals. The locations of the corresponding sources are then estimated with some indeterminancy in the results. It can be seen that the locations of the sources change for a schizophrenic patient. The experimental results verify the statistical significance of the method and its potential application in the diagnosis and monitoring of schizophrenia.
LanguageEnglish
JournalEURASIP Journal on Advances in Signal Processing
DOIs
Publication statusPublished - 2006

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Blind source separation
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title = "Separation and Localisation of P300 Sources and their Subcomponents Using Constrained Blind Source Separation",
abstract = "Separation and localisation of P300 sources and their constituent subcomponents for both visual and audio stimulations is investigated in this paper. An effective constrained blind source separation (CBSS) algorithm is developed for this purpose. The algorithm is an extension of the Infomax BSS system for which a measure of distance between a carefully measured P300 and the estimated sources is used as a constraint. During separation, the proposed CBSS method attempts to extract the corresponding P300 signals. The locations of the corresponding sources are then estimated with some indeterminancy in the results. It can be seen that the locations of the sources change for a schizophrenic patient. The experimental results verify the statistical significance of the method and its potential application in the diagnosis and monitoring of schizophrenia.",
author = "Loukianos Spyrou and Min Jing and Saeid Sanei and Alex Sumich",
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Separation and Localisation of P300 Sources and their Subcomponents Using Constrained Blind Source Separation. / Spyrou, Loukianos ; Jing, Min; Sanei, Saeid; Sumich, Alex .

In: EURASIP Journal on Advances in Signal Processing, 2006.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Separation and Localisation of P300 Sources and their Subcomponents Using Constrained Blind Source Separation

AU - Spyrou, Loukianos

AU - Jing, Min

AU - Sanei, Saeid

AU - Sumich, Alex

PY - 2006

Y1 - 2006

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AB - Separation and localisation of P300 sources and their constituent subcomponents for both visual and audio stimulations is investigated in this paper. An effective constrained blind source separation (CBSS) algorithm is developed for this purpose. The algorithm is an extension of the Infomax BSS system for which a measure of distance between a carefully measured P300 and the estimated sources is used as a constraint. During separation, the proposed CBSS method attempts to extract the corresponding P300 signals. The locations of the corresponding sources are then estimated with some indeterminancy in the results. It can be seen that the locations of the sources change for a schizophrenic patient. The experimental results verify the statistical significance of the method and its potential application in the diagnosis and monitoring of schizophrenia.

U2 - https://doi.org/10.1155/2007/82912

DO - https://doi.org/10.1155/2007/82912

M3 - Article

JO - EURASIP Journal on Advances in Signal Processing

T2 - EURASIP Journal on Advances in Signal Processing

JF - EURASIP Journal on Advances in Signal Processing

SN - 1687-6172

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