Electroencephalography and heart rate variability prognostics in mental health therapies for Malaysian workers

Globally, over a million individuals succumb to suicide annually, with depression contributing to 6.7% of these tragic deaths. Such crises often stem from life-induced pressures, escalating into severe mental health issues. Recognizing these early signs is pivotal, but insufficient without effective therapeutic measures. This study endeavors to address these challenges by exploring patient responses to therapy using electroencephalogram (EEG) and heart rate variability (HRV) data. Conducted in Kuala Terengganu, Malaysia, the research involves workers and employs aromatherapy, deep breathing exercises, and ruqyah alongside a control group. EEG and HRV signals monitor brain wave patterns and heart rhythm coherence, aiding in identifying depression, stress, and anxiety indicators. Integrating questionnaire data including the depression-anxiety-stress-scale (DASS), beck depression inventory (BDI), beck anxiety inventory (BAI), and statistical analysis, the study aims to evaluate therapeutic efficacy in enhancing relaxation and mental well-being. Metrics like HRV coherence ratio and EEG delta wave activity offer insights into therapy optimization. Results suggest deep breathing exercises and aromatherapy as most effective in inducing calmness, followed by ruqyah. By tailoring therapy to individual needs, especially among workers, the study endeavors to foster mental health resilience in communities, paving the path towards a mentally healthier populace.

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Publication Details

Journal
International Journal of Public Health Science (IJPHS)
Published
2025-03-12
DOI
https://doi.org/10.11591/ijphs.v14i2.25224
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
0.00

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Electroencephalography and heart rate variability prognostics in mental health therapies for Malaysian workers

Chong Siew Koon, Samhani Ismail, Nurnadiah Zamri, Norsuhaily Abu Bakar et al.
International Journal of Public Health Science (IJPHS)
EEG and Brain-Computer Interfaces
article

Electroencephalography and heart rate variability prognostics in mental health therapies for Malaysian workers

Chong Siew Koon, Samhani Ismail, Nurnadiah Zamri, Norsuhaily Abu Bakar, Nurul Akmar Abu Bakar, Azimah Ismail, Siti Nurani Hj Hassan, Tuan Sharipah Tuan Hadi, Amir Zulhilmi Yahaya
article en

Abstract

Globally, over a million individuals succumb to suicide annually, with depression contributing to 6.7% of these tragic deaths. Such crises often stem from life-induced pressures, escalating into severe mental health issues. Recognizing these early signs is pivotal, but insufficient without effective therapeutic measures. This study endeavors to address these challenges by exploring patient responses to therapy using electroencephalogram (EEG) and heart rate variability (HRV) data. Conducted in Kuala Terengganu, Malaysia, the research involves workers and employs aromatherapy, deep breathing exercises, and ruqyah alongside a control group. EEG and HRV signals monitor brain wave patterns and heart rhythm coherence, aiding in identifying depression, stress, and anxiety indicators. Integrating questionnaire data including the depression-anxiety-stress-scale (DASS), beck depression inventory (BDI), beck anxiety inventory (BAI), and statistical analysis, the study aims to evaluate therapeutic efficacy in enhancing relaxation and mental well-being. Metrics like HRV coherence ratio and EEG delta wave activity offer insights into therapy optimization. Results suggest deep breathing exercises and aromatherapy as most effective in inducing calmness, followed by ruqyah. By tailoring therapy to individual needs, especially among workers, the study endeavors to foster mental health resilience in communities, paving the path towards a mentally healthier populace.

International Journal of Public Health Science (IJPHS)Vol. 14(2)
Hospital Kuala Lumpur (MY), Hospital Sultanah Nur Zahirah (MY), National Institute of Occupational Safety and Health (JP), Sultan Zainal Abidin University (MY)
Universiti Sultan Zainal Abidin, National Institute for Occupational Safety and Health
Openalex Percentile: Top 96%
EEG and Brain-Computer Interfaces
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