eprintid: 3700
rev_number: 8
eprint_status: archive
userid: 17
dir: disk0/00/00/37/00
datestamp: 2019-12-04 07:18:12
lastmod: 2019-12-04 07:18:12
status_changed: 2019-12-04 07:18:12
type: conference_item
metadata_visibility: show
creators_name: Le, Thanh Xuyen
creators_name: Le, Trung Thanh
creators_name: Nguyen, Linh Trung
creators_name: Tran, Thi Thuy Quynh
creators_name: Nguyen, Duc Thuan
creators_id: xuyen.lethanh@hust.edu.vn
creators_id: letrungthanhtbt@gmail.com
creators_id: linhtrung@vnu.edu.vn
creators_id: quynhttt@vnu.edu.vn
creators_id: thuan.nguyenduc@hust.edu.vn
title: EEG tensor representation using graph signal processing
ispublished: pub
subjects: ECE
subjects: IT
divisions: avitech
divisions: fac_fet
abstract: To help analyze electroencephalography (EEG) data for epilepsy, we propose a temporal–spatial–spectral tensor tensor representation for epileptic spikes via graph signal processing. Instead of using the temporal behavior of the sources, we apply the graph wavelet transform to the spatial variable for constructing the new representation of the epilepsy tensor, in order to exploit latent information of the spatial domain. To illustrate the usefulness of the proposed method for EEG tensor representation, we decompose this tensor to separate EEG sources. Simulation results on real EEG data of a patient diagnosed of epilepsy indicated that our proposed method of representation is promising in estimating the epileptic sources.
date: 2019-11-21
date_type: published
contact_email: linhtrung@vnu.edu.vn
full_text_status: none
pres_type: paper
event_title: 2019 KICS Korea-Vietnam International Joint Workshop on Communications and Information Sciences
event_location: Hanoi, Vietnam
event_dates: 21-22 November, 2019
event_type: conference
refereed: TRUE
citation:   Le, Thanh Xuyen and Le, Trung Thanh and Nguyen, Linh Trung and Tran, Thi Thuy Quynh and Nguyen, Duc Thuan  (2019) EEG tensor representation using graph signal processing.  In: 2019 KICS Korea-Vietnam International Joint Workshop on Communications and Information Sciences, 21-22 November, 2019, Hanoi, Vietnam.