@inproceedings{scholars8947, year = {2017}, doi = {10.1109/ICIAS.2016.7824097}, note = {cited By 5; Conference of 6th International Conference on Intelligent and Advanced Systems, ICIAS 2016 ; Conference Date: 15 August 2016 Through 17 August 2016; Conference Code:125970}, publisher = {Institute of Electrical and Electronics Engineers Inc.}, journal = {International Conference on Intelligent and Advanced Systems, ICIAS 2016}, title = {Using resting state coherence to distinguish between low and high stress groups}, author = {Subhani, A. R. and Malik, A. S. and Kamil, N. and Naufal, M. and Saad, M.}, isbn = {9781509008452}, keywords = {Brain; Electroencephalography, Brain connectivity; Eeg coherences; Electroencephalographic (EEG); Information flows; Mathematical representations; Mental stress; Perceived Stress Scale; Resting state, Crosstalk}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85011990385&doi=10.1109\%2fICIAS.2016.7824097&partnerID=40&md5=346050f8a71d8b65a8991b3f9ffa5828}, abstract = {Mental stress that is originated due to high task demands affects our life. Human brain is a target of stress. Neuronal variations take place in the brain and make many brain regions communicate with each other to process the information flow. Electroencephalographic (EEG) coherence is a mathematical representation of cross talk between two brain regions. This paper aims to explore the irregularities in EEG coherence due to the exposure of mental stress. Furthermore, this paper also explores the difference in brain connectivity between low-stress and high-stress subjects. Twenty-two subjects were exposed to a stressful situation for twenty minutes. Their EEG was recorded and compared in pre-and post-stress rest conditions to mark irregularities in EEG coherence. The distinction of subjects in low-and high-stress was done based on their score in the Perceived Stress Scale (PSS). {\^A}{\copyright} 2016 IEEE.} }