TY - GEN
T1 - Mental Stress Analysis using the Power Spectrum of fNIRS Signals
AU - Katmah, Rateb
AU - Al-Shargie, Fares
AU - Tariq, Usman
AU - Babiloni, Fabio
AU - Al-Mughairbi, Fadwa
AU - Al-Nashash, Hasan
N1 - Funding Information:
ACKNOWLEDGMENT The authors like to convey their appreciation to all subjects who participated in this study for their devotion during the fNIRS recording. The American University of Sharjah, United Arab Emirate, financed this research through the FRG20-LE25 research grant.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Mental stress is one of the major health problems in modern societies. Detecting mental stress at its early stage and developing a method of stress mitigation is very important for safety, health and quality of life. In this study, we employed a modified Stroop Color Word Task (SCWT) with time constrains and negative feedback about the performance, together with Binaural Beats Stimulation (BBs), to induce three varied levels of mental stress. Level one was based on SCWT alone and level two was based on SCWT+time-pressure and level three was by utilizing SCWT+time-pressure+BBs. We then quantified the level of stress using a NASA TLX questionnaire and functional near-infrared spectroscopy (fNIRS). The fNIRS signals were then analyzed using the Welch power spectrum density (PSD) to investigate the discrepancy in brain activity across the three levels of mental stress. We found that the mean PSD value in the frequency range of 0.2 to 0.5 Hz has significantly changed between the three stress levels. These findings indicate that the fNIRS power spectrum analysis method could be used as a robust marker for mental stress.
AB - Mental stress is one of the major health problems in modern societies. Detecting mental stress at its early stage and developing a method of stress mitigation is very important for safety, health and quality of life. In this study, we employed a modified Stroop Color Word Task (SCWT) with time constrains and negative feedback about the performance, together with Binaural Beats Stimulation (BBs), to induce three varied levels of mental stress. Level one was based on SCWT alone and level two was based on SCWT+time-pressure and level three was by utilizing SCWT+time-pressure+BBs. We then quantified the level of stress using a NASA TLX questionnaire and functional near-infrared spectroscopy (fNIRS). The fNIRS signals were then analyzed using the Welch power spectrum density (PSD) to investigate the discrepancy in brain activity across the three levels of mental stress. We found that the mean PSD value in the frequency range of 0.2 to 0.5 Hz has significantly changed between the three stress levels. These findings indicate that the fNIRS power spectrum analysis method could be used as a robust marker for mental stress.
KW - Mental Stress
KW - SCWT
KW - Welch power spectrum
KW - fNIRS
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U2 - 10.1109/ICECTA57148.2022.9990237
DO - 10.1109/ICECTA57148.2022.9990237
M3 - Conference contribution
AN - SCOPUS:85146366617
T3 - 2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022
SP - 216
EP - 219
BT - 2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2022
Y2 - 23 November 2022 through 25 November 2022
ER -