Improved ballistocardiac artifact removal from the electroencephalogram recorded in fMRI

Kyung Hwan Kim, Hyo Woon Yoon, Hyun Wook Park

Research output: Contribution to journalArticle

66 Citations (Scopus)

Abstract

The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance image (fMRI) is a promising tool that is capable of providing high spatiotemporal brain mapping, with each modality supplying complementary information. One of the major barriers to obtain high-quality simultaneous EEG/fMRI data is that pulsatile activity due to the heartbeat induces significant artifacts in the EEG. The purpose of this study was to develop a novel algorithm for removing heartbeat artifact, thus overcoming problems associated with previous methods. Our method consists of a mean artifact wave form subtraction, the selective removal of wavelet coefficients, and a recursive least-square adaptive filtering. The recursive least-square adaptive filtering operates without dedicated sensor for the reference signal, and only when the mean subtraction and wavelet-based noise removal is not satisfactory. The performance of our system has been assessed using simulated data based on experimental data of various spectral characteristics, and actual experimental data of alpha-wave-dominant normal EEG and epileptic EEG.

Original languageEnglish
Pages (from-to)193-203
Number of pages11
JournalJournal of Neuroscience Methods
Volume135
Issue number1-2
DOIs
Publication statusPublished - 2004 May 30

Fingerprint

Artifacts
Electroencephalography
Magnetic Resonance Spectroscopy
Least-Squares Analysis
Brain Mapping
Noise

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)

Cite this

@article{7a68a0c41cb64e2285db3b696442f9f7,
title = "Improved ballistocardiac artifact removal from the electroencephalogram recorded in fMRI",
abstract = "The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance image (fMRI) is a promising tool that is capable of providing high spatiotemporal brain mapping, with each modality supplying complementary information. One of the major barriers to obtain high-quality simultaneous EEG/fMRI data is that pulsatile activity due to the heartbeat induces significant artifacts in the EEG. The purpose of this study was to develop a novel algorithm for removing heartbeat artifact, thus overcoming problems associated with previous methods. Our method consists of a mean artifact wave form subtraction, the selective removal of wavelet coefficients, and a recursive least-square adaptive filtering. The recursive least-square adaptive filtering operates without dedicated sensor for the reference signal, and only when the mean subtraction and wavelet-based noise removal is not satisfactory. The performance of our system has been assessed using simulated data based on experimental data of various spectral characteristics, and actual experimental data of alpha-wave-dominant normal EEG and epileptic EEG.",
author = "Kim, {Kyung Hwan} and Yoon, {Hyo Woon} and Park, {Hyun Wook}",
year = "2004",
month = "5",
day = "30",
doi = "10.1016/j.jneumeth.2003.12.016",
language = "English",
volume = "135",
pages = "193--203",
journal = "Journal of Neuroscience Methods",
issn = "0165-0270",
publisher = "Elsevier",
number = "1-2",

}

Improved ballistocardiac artifact removal from the electroencephalogram recorded in fMRI. / Kim, Kyung Hwan; Yoon, Hyo Woon; Park, Hyun Wook.

In: Journal of Neuroscience Methods, Vol. 135, No. 1-2, 30.05.2004, p. 193-203.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Improved ballistocardiac artifact removal from the electroencephalogram recorded in fMRI

AU - Kim, Kyung Hwan

AU - Yoon, Hyo Woon

AU - Park, Hyun Wook

PY - 2004/5/30

Y1 - 2004/5/30

N2 - The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance image (fMRI) is a promising tool that is capable of providing high spatiotemporal brain mapping, with each modality supplying complementary information. One of the major barriers to obtain high-quality simultaneous EEG/fMRI data is that pulsatile activity due to the heartbeat induces significant artifacts in the EEG. The purpose of this study was to develop a novel algorithm for removing heartbeat artifact, thus overcoming problems associated with previous methods. Our method consists of a mean artifact wave form subtraction, the selective removal of wavelet coefficients, and a recursive least-square adaptive filtering. The recursive least-square adaptive filtering operates without dedicated sensor for the reference signal, and only when the mean subtraction and wavelet-based noise removal is not satisfactory. The performance of our system has been assessed using simulated data based on experimental data of various spectral characteristics, and actual experimental data of alpha-wave-dominant normal EEG and epileptic EEG.

AB - The simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance image (fMRI) is a promising tool that is capable of providing high spatiotemporal brain mapping, with each modality supplying complementary information. One of the major barriers to obtain high-quality simultaneous EEG/fMRI data is that pulsatile activity due to the heartbeat induces significant artifacts in the EEG. The purpose of this study was to develop a novel algorithm for removing heartbeat artifact, thus overcoming problems associated with previous methods. Our method consists of a mean artifact wave form subtraction, the selective removal of wavelet coefficients, and a recursive least-square adaptive filtering. The recursive least-square adaptive filtering operates without dedicated sensor for the reference signal, and only when the mean subtraction and wavelet-based noise removal is not satisfactory. The performance of our system has been assessed using simulated data based on experimental data of various spectral characteristics, and actual experimental data of alpha-wave-dominant normal EEG and epileptic EEG.

UR - http://www.scopus.com/inward/record.url?scp=1542723008&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=1542723008&partnerID=8YFLogxK

U2 - 10.1016/j.jneumeth.2003.12.016

DO - 10.1016/j.jneumeth.2003.12.016

M3 - Article

C2 - 15020103

AN - SCOPUS:1542723008

VL - 135

SP - 193

EP - 203

JO - Journal of Neuroscience Methods

JF - Journal of Neuroscience Methods

SN - 0165-0270

IS - 1-2

ER -