This research project aims to tackle the growing mental health challenges in today's digital age. It employs a modified pre-trained BERT model to detect depressive text within social media and users' web browsing data, achieving an impressive 93% test accuracy. Simultaneously, the project aims to incorporate physiological signals from wearable devices, such as smartwatches and EEG sensors, to provide long-term tracking and prognosis of mood disorders and emotional states. This comprehensive approach holds promise for enhancing early detection of depression and advancing overall mental health outcomes.
@article{arxiv.2401.13722,
title = {Proactive Emotion Tracker: AI-Driven Continuous Mood and Emotion Monitoring},
author = {Mohammad Asif and Sudhakar Mishra and Ankush Sonker and Sanidhya Gupta and Somesh Kumar Maurya and Uma Shanker Tiwary},
journal= {arXiv preprint arXiv:2401.13722},
year = {2024}
}