eprintid: 5632
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/56/32
datestamp: 2023-11-09 16:17:22
lastmod: 2023-11-09 16:17:22
status_changed: 2023-11-09 16:03:23
type: conference_item
metadata_visibility: show
creators_name: Ahmad, R.F.
creators_name: Malik, A.S.
creators_name: Kamel, N.
creators_name: Reza, F.
title: Object categories specific brain activity classification with simultaneous EEG-fMRI
ispublished: pub
keywords: adult; brain; brain mapping; electroencephalography; human; multimodal imaging; nuclear magnetic resonance imaging; pattern recognition; physiology, Adult; Brain; Brain Mapping; Electroencephalography; Humans; Magnetic Resonance Imaging; Multimodal Imaging; Pattern Recognition, Visual
note: cited By 3; Conference of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2015 ; Conference Date: 25 August 2015 Through 29 August 2015; Conference Code:116805
abstract: Any kind of visual information is encoded in terms of patterns of neural activity occurring inside the brain. Decoding neural patterns or its classification is a challenging task. Functional magnetic resonance imaging (fMRI) and Electroencephalography (EEG) are non-invasive neuroimaging modalities to capture the brain activity pattern in term of images and electric potential respectively. To get higher spatiotemporal resolution of human brain from these two complementary neuroimaging modalities, simultaneous EEG-fMRI can be helpful. In this paper, we proposed a framework for classifying the brain activity patterns with simultaneous EEG-fMRI. We have acquired five human participants' data with simultaneous EEG-fMRI by showing different object categories. Further, combined analysis of EEG and fMRI data was carried out. Extracted information through combine analysis is passed to support vector machine (SVM) classifier for classification purpose. We have achieved better classification accuracy using simultaneous EEG-fMRI i.e., 81.8 as compared to fMRI data standalone. This shows that multimodal neuroimaging can improve the classification accuracy of brain activity patterns as compared to individual modalities reported in literature. © 2015 IEEE.
date: 2015
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84953248170&doi=10.1109%2fEMBC.2015.7318735&partnerID=40&md5=3a8929c8f1fd4578d588d6e3e5c82d29
id_number: 10.1109/EMBC.2015.7318735
full_text_status: none
publication: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
volume: 2015-N
pagerange: 1825-1828
refereed: TRUE
isbn: 9781424492718
issn: 1557170X
citation:   Ahmad, R.F. and Malik, A.S. and Kamel, N. and Reza, F.  (2015) Object categories specific brain activity classification with simultaneous EEG-fMRI.  In: UNSPECIFIED.