Stress Detection in Working Professionals

Digital workplace demands high levels of productivity, often at the cost of levels of employee well-being. The stress that builds up in professionals over time, if left unchecked, can harm mental health and reduce efficiency. This project focuses on developing an intelligent system that automatically identifies stress in working professionals by analysing facial expressions through image processing, utilizing Recurrent Neural Networks (RNNs). This paper gathers real-time images from various office environments, use RNNs to model time-based features and detect stress patterns with remarkable accuracy. The system aims to contribute to a supportive organizational culture by enabling early interventions and enhancing overall employee productivity.