Monitoring Emotional Response During Mental Health Therapy Monitoring Emotional Response During Mental Health Therapy

Resumen

Facial emotion recognition is one of the most complex problems in computer vision, due to multiple factors ranging from image brightness to the personality of the individual. This paper built and elucidates the implementation of facial expression recognition solutions, an open-source package called FFEM to easily perform this task, and an application that integrates the previous package, using state-of-the-art models and algorithms for facial detection and emotion recognition mainly coming from MediaPipe and DeepFace with the intention of addressing the challenge of recognizing patients' emotions during cognitive therapy sessions. However, the versatility of this approach allows it to be applied to different industries and tasks, highlighting its potential for diverse use cases.