eprintid: 2593
rev_number: 17
eprint_status: archive
userid: 12
dir: disk0/00/00/25/93
datestamp: 2017-10-29 07:23:52
lastmod: 2018-01-10 07:57:24
status_changed: 2018-01-10 07:57:24
type: conference_item
metadata_visibility: show
creators_name: Pham Van, Thanh
creators_name: Dang Nhu, Dinh
creators_name: Nguyen Duc, Anh
creators_name: Nguyen Tien, Anh
creators_name: Chu Duc, Hoang
creators_name: Tran, Duc Tan
creators_id: phamvanthanh1209@gmail.com
creators_id: dangnhu@gmail.com
creators_id: anhnd@gmail.com
creators_id: anhnt007@gmail.com
creators_id: hoangcd@gmail.com
creators_id: tantd@vnu.edu.vn
title: Automatic removal of EOG artifacts using SOBI algorithm combined with intelligent source identification technique
ispublished: pub
subjects: ElectronicsandComputerEngineering
divisions: fac_fet
abstract: Electrooculography (EOG) artifacts, generated by winking or other eye’s movements, should be eliminated because they are the cause of the wrong decision in analysis the Electroencephalography (EEG) data, especially in the diagnosis of epilepsy. One of the efficient methods for signal separation is the Second order blind identification (SOBI), a blind source separation technique. In most cases, the activities of the two eyes are the same, and SOBI identify that there is only one source of artifact. However, in some cases, the activities of the two eyes are different, and SOBI identify that there are two different sources of artifacts [1]. The problem is that SOBI cannot provide the information about the order of sources. It means that, it cannot point out how many sources of EOG. It would lead to the wrong decision in EEG analysis. To solve this current limitation, in this paper, we propose an effective method to remove EOG from EEG using SOBI combined with intelligent source identification technique. The proposed method was evaluated carefully using experimental data. It determined successfully the number of EOG sources and removes these artifacts more accurately and efficiently.
date: 2017-10-18
date_type: published
official_url: http://atc-conf.org
full_text_status: public
pres_type: lecture
pagerange: 260-264
event_title: International Conference on Advanced Technologies for Communications
event_location: Quy Nhon, Viet Nam
event_dates: Oct., 18-20, 2017
event_type: conference
refereed: TRUE
related_url_url: http://atc-conf.org
citation:   Pham Van, Thanh and Dang Nhu, Dinh and Nguyen Duc, Anh and Nguyen Tien, Anh and Chu Duc, Hoang and Tran, Duc Tan  (2017) Automatic removal of EOG artifacts using SOBI algorithm combined with intelligent source identification technique.  In: International Conference on Advanced Technologies for Communications, Oct., 18-20, 2017, Quy Nhon, Viet Nam.     
document_url: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2593/1/p260-pham.pdf