A robust independent component analysis algorithm for removing ballistocardiogram artifacts from EEG and fMRI recordings

Tiziana Franchin; A. M. Bianchi; V. Cannatà; E. Genovese; F. Nocchi; S. Cerutti

doi:10.1007/978-3-540-89208-3_306

A robust independent component analysis algorithm for removing ballistocardiogram artifacts from EEG and fMRI recordings

Tiziana Franchin, A. M. Bianchi, V. Cannatà, E. Genovese, F. Nocchi, S. Cerutti

Ospedale Pediatrico Bambino Gesu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings provide complementary advantages with regard to the temporal and spatial resolution of brain activity. This methodology still now suffers from several artifacts, such as the gradient, the ballistocardiogram (BCG) and electrooculogram (EOG). A number of procedures have been developed in recent years for removing BCG artifacts and the usefulness of Independent Component Analysis (ICA) in this purpose was largely discussed and demonstrated. The aim of this study is to propose a more efficient and robust independent component analysis algorithm (RobustICA) for removing BCG and EOG artifacts. The algorithm has been validated on EEG datasets acquired inside the static magnetic field of a 1,5 T RM scanner and its performances were compared with those of other already applied processing methods (Optimal Basis Set, FastICA).

Original language	English
Title of host publication	IFMBE Proceedings
Pages	1286-1289
Number of pages	4
Volume	22
DOIs	https://doi.org/10.1007/978-3-540-89208-3_306
Publication status	Published - 2008
Event	4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008 - Antwerp, Belgium Duration: Nov 23 2008 → Nov 27 2008

Other

Other	4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008
Country/Territory	Belgium
City	Antwerp
Period	11/23/08 → 11/27/08

Keywords

Ballistocardiogram artifact
EEG
FMRI
ICA

ASJC Scopus subject areas

Biomedical Engineering
Bioengineering

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10.1007/978-3-540-89208-3_306

Cite this

Franchin, T, Bianchi, AM, Cannatà, V , Genovese, E, Nocchi, F & Cerutti, S 2008, A robust independent component analysis algorithm for removing ballistocardiogram artifacts from EEG and fMRI recordings. in IFMBE Proceedings. vol. 22, pp. 1286-1289, 4th European Conference of the International Federation for Medical and Biological Engineering, ECIFMBE 2008, Antwerp, Belgium, 11/23/08. https://doi.org/10.1007/978-3-540-89208-3_306

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abstract = "Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings provide complementary advantages with regard to the temporal and spatial resolution of brain activity. This methodology still now suffers from several artifacts, such as the gradient, the ballistocardiogram (BCG) and electrooculogram (EOG). A number of procedures have been developed in recent years for removing BCG artifacts and the usefulness of Independent Component Analysis (ICA) in this purpose was largely discussed and demonstrated. The aim of this study is to propose a more efficient and robust independent component analysis algorithm (RobustICA) for removing BCG and EOG artifacts. The algorithm has been validated on EEG datasets acquired inside the static magnetic field of a 1,5 T RM scanner and its performances were compared with those of other already applied processing methods (Optimal Basis Set, FastICA).",

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AU - Franchin, Tiziana

AU - Bianchi, A. M.

AU - Cannatà, V.

AU - Genovese, E.

AU - Nocchi, F.

AU - Cerutti, S.

PY - 2008

Y1 - 2008

N2 - Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings provide complementary advantages with regard to the temporal and spatial resolution of brain activity. This methodology still now suffers from several artifacts, such as the gradient, the ballistocardiogram (BCG) and electrooculogram (EOG). A number of procedures have been developed in recent years for removing BCG artifacts and the usefulness of Independent Component Analysis (ICA) in this purpose was largely discussed and demonstrated. The aim of this study is to propose a more efficient and robust independent component analysis algorithm (RobustICA) for removing BCG and EOG artifacts. The algorithm has been validated on EEG datasets acquired inside the static magnetic field of a 1,5 T RM scanner and its performances were compared with those of other already applied processing methods (Optimal Basis Set, FastICA).

AB - Simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) recordings provide complementary advantages with regard to the temporal and spatial resolution of brain activity. This methodology still now suffers from several artifacts, such as the gradient, the ballistocardiogram (BCG) and electrooculogram (EOG). A number of procedures have been developed in recent years for removing BCG artifacts and the usefulness of Independent Component Analysis (ICA) in this purpose was largely discussed and demonstrated. The aim of this study is to propose a more efficient and robust independent component analysis algorithm (RobustICA) for removing BCG and EOG artifacts. The algorithm has been validated on EEG datasets acquired inside the static magnetic field of a 1,5 T RM scanner and its performances were compared with those of other already applied processing methods (Optimal Basis Set, FastICA).

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KW - EEG

KW - FMRI

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A robust independent component analysis algorithm for removing ballistocardiogram artifacts from EEG and fMRI recordings

Abstract

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Keywords

ASJC Scopus subject areas

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