%0 Conference Paper
%A Al-Shargie, F.
%A Tang, T.B.
%A Badruddin, N.
%A Dass, S.C.
%A Kiguchi, M.
%D 2017
%F scholars:8956
%I Institute of Electrical and Electronics Engineers Inc.
%K Feedback; Infrared devices; Near infrared spectroscopy; Support vector machines, Detection rates; Electro-encephalogram (EEG); Feature level fusion; Functional near-infrared spectroscopy (fnirs); Individual performance; Prefrontal cortex; Simultaneous measurement; Stress condition, Electroencephalography
%R 10.1109/ICIAS.2016.7824060
%T Mental stress assessment based on feature level fusion of fNIRS and EEG signals
%U https://khub.utp.edu.my/scholars/8956/
%X This study aims to improve the detection rate of mental stress using the complementary nature of functional Near Infrared Spectroscopy (fNIRS) and Electroencephalogram (EEG). Simultaneous measurements of fNIRS and EEG signals were conducted on 12 subjects while solving arithmetic problems under two different conditions (control and stress). The stressors in this work were time pressure and negative feedback of individual performance. The study demonstrated significant reduction in the concentration of oxygenated haemoglobin (p=0.0032) and alpha rhythm power (p=0.0213) on the prefrontal cortex (PFC) under stress condition. Specifically, the right PFC and dorsolateral PFC were highly sensitive to mental stress. Using support vector machine (SVM), the mean detection rate of mental stress was 91, 95 and 98 using fNIRS, EEG and fusion of fNIRS and EEG signals, respectively. © 2016 IEEE.
%Z cited By 12; Conference of 6th International Conference on Intelligent and Advanced Systems, ICIAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125970