PMAP: A Multimodal Tool for Visual Analysis of Physiological Biomarkers and Audio for Student Mental Health

This study introduces the PMAP (Physiological Metrics and Audio Platform), an innovative tool designed to support early detection of emotional crises in university students by visualizing key physiological biomarkers alongside audio data. This platform integrates noninvasive measures, including heart rate, body temperature, and audio-based vocal patterns, to offer a preliminary view into emotional states, aiming to improve mental health resources in higher education. Utilizing the Embrace Plus device, biometric data was collected under controlled conditions and processed using Python-based artificial intelligence libraries for visual representation, it provides an essential foundation for monitoring and assessment. Key results indicate the effectiveness of the platform in offering clear, organized visualizations of physiological responses associated with stress and emotional triggers. Future enhancements will incorporate machine learning algorithms to enable real-time monitoring and interpretation, enhancing the effectiveness of the platform for mental health professionals. This approach not only addresses limitations in accessibility and objectivity within traditional diagnostics but also advances a proactive, data-driven model for mental health support in academic settings, promoting timely, individualized interventions.