Proactive Emotion Tracker: AI-Driven Continuous Mood and Emotion Monitoring

• URL: http://arxiv.org/abs/2401.13722v1
• Date: Wed, 24 Jan 2024 15:05:11 GMT
• Title: Proactive Emotion Tracker: AI-Driven Continuous Mood and Emotion Monitoring
• Authors: Mohammad Asif, Sudhakar Mishra, Ankush Sonker, Sanidhya Gupta, Somesh Kumar Maurya and Uma Shanker Tiwary
• Abstract summary: The 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.
• Score: 2.271910267215261
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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