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LCMV-Based EEG & FNIRS-Based Brain Source Localization of Mental Stress
Almadani, Ismat Feras Ismat
Almadani, Ismat Feras Ismat
Date
2024-05
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Type
Thesis
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Description
A Master of Science thesis in Biomedical Engineering by Ismat Feras Ismat Almadani entitled, “LCMV-Based EEG & FNIRS-Based Brain Source Localization of Mental Stress”, submitted in May 2024. Thesis advisor is Dr. Hasan Mir and thesis co-advisor is Dr. Hasan Al-Nashash. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
Abstract
Mental stress is a significant health concern, characterized by emotional and psychological pressure induced by challenging or threatening situations. Stress contributes to various psychophysiological disorders like depression, strokes, and cardiac issues. Current research employs electroencephalogram (EEG) signals for early-stage mental stress detection, exploiting the high temporal resolution of EEG. However, due to its poor spatial resolution, EEG cannot reveal the precise position of the brain activity's source. This necessitates the employment of signal processing methods to identify the brain region where the activity originated. The forward problem and the inverse problem that make up this localization problem must both be solved in order to determine the source's position. In this thesis, an experiment was conducted by the neuroengineering team at the American University of Sharjah that collected EEG and functional near infrared spectroscopy (fNIRS) data, along with participants' responses to a questionnaire and saliva samples to measure cortisol levels, from a cohort of 21 subjects. All participants were employed individuals with daily office work routines known to induce mental stress. The purpose of this study is to use the collected EEG data to localize the sources of the mental stress in the cortex of the brain and use the fNIRS data as a ground truth for the location of the source. To perform brain source localization using EEG signals, the Linearly Constrained Minimum Variance (LCMV) is used due to its advantages over other localization methods. This research seeks to advance the understanding of the neural nature of mental stress, contributing to the development of more effective stress management techniques. Results show that the LCMV-based approach successfully localized the sources of mental stress in the cortex of the brain, as validated by the fNIRS data. Also, the paired t-test applied on cortisol concentrations showed a significant difference in stress levels between the morning and evening phases. This advancement in understanding stress neurology offers potential for personalized interventions, enhancing mental health outcomes.