Privacy Preserving Emotion and Stress Detection using Multimodal Analysis

Although there are commercially available wearable devices that can collect physiological data, it is still a challenge to accurately translate it into accurate diagnoses of psychological conditions such as stress, anxiety, emotions, etc. This project aims to develop an AI model that detects stress and emotions from these data streams while ensuring user privacy. By combining signal processing and machine learning, the system analyzes various markers to identify emotional states and stress levels. It empowers individuals to manage their emotional well-being and offers valuable insights for mental health professionals, promoting emotional intelligence and stress resilience through a non-invasive, user-friendly solution.

Team Members: Mohammad Fasiul Abedin Khan, Muntaha Majed Chowdhury, Md Golam Tawhid Fahad, Nusrat Sultana, Md Jobayer, Sumaiya Akter, Md. Mehedi Hasan Shawon.