eprintid: 8383
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/00/83/83
datestamp: 2023-11-09 16:20:17
lastmod: 2023-11-09 16:20:17
status_changed: 2023-11-09 16:12:31
type: article
metadata_visibility: show
creators_name: Al-Shargie, F.
creators_name: Tang, T.B.
creators_name: Kiguchi, M.
title: Stress Assessment Based on Decision Fusion of EEG and fNIRS Signals
ispublished: pub
keywords: Curve fitting; Electroencephalography; Electrophysiology; Infrared devices; Near infrared spectroscopy; Neuroimaging; Probes; Stresses; Support vector machines, Atmospheric measurement; Decision fusion; Functional near-infrared spectroscopy (fnirs); Mental arithmetic; Particle measurement; Receiver operating characteristic curves; Spatial resolution; Stress assessment, Functional neuroimaging
note: cited By 60
abstract: Fusion of electroencephalography (EEG) and functional near infrared spectroscopy (fNIRS) is an emerging approach in the field of psychological and neurological studies. We developed a decision fusion technique to combine the output probabilities of the EEG and fNIRS classifiers. The fusion explored support vector machine as classifier for each modality, and optimized the classifiers based on their receiver operating characteristic curve values. EEG and fNIRS signal were acquired simultaneously while performing mental arithmetic task under control and stress conditions. Experiment results from 20 subjects demonstrated significant improvement in the detection rate of mental stress by +7.76 ( p<0.001) and +10.57 ( p<0.0005), compared with sole modality of EEG and fNIRS, respectively. © 2013 IEEE.
date: 2017
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030634505&doi=10.1109%2fACCESS.2017.2754325&partnerID=40&md5=8f187f3d8b0e0df4305a465b1637a258
id_number: 10.1109/ACCESS.2017.2754325
full_text_status: none
publication: IEEE Access
volume: 5
pagerange: 19889-19896
refereed: TRUE
issn: 21693536
citation:   Al-Shargie, F. and Tang, T.B. and Kiguchi, M.  (2017) Stress Assessment Based on Decision Fusion of EEG and fNIRS Signals.  IEEE Access, 5.  pp. 19889-19896.  ISSN 21693536