Emotion Recognition System For Mental Health Monitoring

Abstract: Recognizing and identifying emotions is a key element of understanding mental health that can ideally lead to better emotional well-being. The project combines facial recognition of emotions with data analysis to assess for conditions such as anxiety and depression. This detects and provides real-time emotion profiles with individual perspectives for healthcare workers via deep learning. To detect facial expression, Convolutional Neural Networks (CNNs) are utilized along a series of facial characteristics to extract essential details. Artificial Neural Networks can be made to classify emotions and, thus, play a role in understanding patterns related to mental health conditions; e.g., feeling drowsy, anxious. This system essentially links technology and health care, effectively equipping mental health professionals with modern, data-driven tools for on-time and personalized interventions.

Keywords: Artificial Neural Network, Convolutional Neural Network.