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Author: search.filters.author.Phairot, EkkaponSubject: search.filters.subject.Electroencephalography (EEG)

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    Alleviating Chronic Stress in University Students: An EEG Analysis of Binaural Beat Therapy
    (2025-01-01)
    Aunchit, Sasithon
    ;
    Angsuwatanakul, Thanate
    ;
    Phairot, Ekkapon
    ;
    Jinawan, Chulikon
    ;
    Sirirattanapan, Boonrut
    The COVID-19 pandemic has significantly elevated chronic stress levels, especially among university students. This study examined the effectiveness of binaural beat auditory stimulation in reducing chronic stress, using both the DASS-21 questionnaire and electroencephalography (EEG) as measurement tools. Six students identified with high stress were randomly assigned to one of three four-week interventions: alpha binaural beat music, beta binaural beat music, or non-binaural beat control music. EEG analysis revealed a general increase in power spectrum across all groups, indicating changes in brainwave activity. Notably, a significant increase in sample entropy—a measure of neural complexity—was observed exclusively in the alpha binaural beat group by week four. Correspondingly, this group showed the greatest reduction in self-reported DASS-21 stress scores. These findings suggest that alpha binaural beat stimulation promotes effective neural entrainment and is more successful than beta or non-binaural beat stimuli in alleviating chronic stress among university students. This study highlights the potential of binaural beat auditory stimulation as a non-invasive tool for improving mental health.
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    Brain Function Analysis Using EEG Evidence: New Insights into English Paper-Based Versus Computer-Based Tests
    (2024-01-01)
    Khemanuwong, Thapanee
    ;
    Angsuwatanakul, Thanate
    ;
    Phairot, Ekkapon
    ;
    Iramina, Keiji
    ;
    Puttasakul, Tasawan
    In today's disruptive era, where digital systems and the internet are central, assessment methods are transitioning from paper-based to computer-based tests. As digital technology becomes more accessible, there is growing interest in determining whether these new formats provide more effective means of evaluating learning outcomes. To investigate this, we examined performance and objective measures of brain function during both computer-based and paper-based reading comprehension tests. This study focuses on brain function analysis of computer-based and paper-based tests measured by EEG signals. Five healthy students at the Bl CEFR level voluntarily participated in two experimental conditions: paper-based testing (PBT) and computer-based testing (CBT). During the tests, EEG signals were recorded and analyzed using MATLAB to identify various features of brain activity. The results indicate that participants who performed better on paper-based tests showed greater familiarity with the test format. The power spectral density of EEG recordings, along with the average frequency of alpha and beta waves, were positively correlated with test familiarity. Specifically, the correlation coefficients were as follows: CBT-difficult (r=0.82, p < 0.05), CBT -easy (r=0.82,p < 0.05), PBT -difficult (r=0.82, p < 0.05), and PBT -easy (r=0.65,p < 0.05).