Abstract ID: 226
Authors:
Farizah Mohd Hairi
Amer Siddiq Amer Nordin
Azmawaty Mohamad Nor
Kalaivane Kannadasan
Mohd Hafyzuddin Md Yusuf
Nur Amani Natasha Ahmad Tajuddin
Siti Idayu Hasan
Affiliations:
Department of Social and Preventive Medicine, Faculty of Medicine, Universiti Malaya; Department of Psychological Medicine, Faculty of Medicine, Universiti Malaya; Department of Emergency Medicine, Faculty of Medicine, Universiti Malaya; Department of Primary Care Medicine, Faculty of Medicine, Universiti Malaya; Faculty of Education, Universiti Malaya; Jempol District Health Office, Negeri Sembilan
Abstract:Background: Mental health challenges are a growing concern globally, often exacerbated by urbanisation, social inequities, and limited access to preventive services. Traditional screenings remain underutilised due to stigma and accessibility barriers. There is an urgent need for scalable, non-invasive tools that promote early detection and equity in mental wellbeing, aligned with the principles of planetary health. Objectives: This pilot study aimed to test the feasibility of using voice and EEG (brainwave) biomarkers to generate personalised mind-health reports for early identification of psychological distress among working adults. Materials and Methods: A multidisciplinary team recruited 30 working adults who completed standardised mental health screening (Whooley questions) and a lifestyle assessment. Guided voice recordings and portable EEG data were collected in controlled settings. Supervised machine learning models were used to analyse vocal features (pitch, jitter, rhythm) and EEG patterns (alpha, beta, theta waves), informing tailored recommendations for lifestyle modifications such as sleep, diet, and stress management. Results: Participants with higher stress levels exhibited flattened vocal prosody and elevated beta/low alpha brain activity. The personalised mind-health reports were found to be acceptable and relevant by users, with positive feedback on clarity and usefulness for self-monitoring. Conclusions: This study demonstrates that integrating voice and EEG biomarkers with lifestyle profiling is a promising approach for equitable, preventive mental health screening. It supports shared solutions across workplaces, schools, and communities through a user-friendly, non-stigmatising platform, aligning with the global call for planetary health equity.
Keywords: Mental Health, Mental Health Screening, Digital Biomarkers, Voice and EEG Analysis, Lifestyle Medicine, Planetary Health Equity
