Altered emotion recognition from psychiatric patient profiles using Machine Learning

Mental illnesses influence the emotion recognition capabilities of those who suffer them.This article presents a study that involves the prediction, using multi-class classification models, of several human standard emotions from facial expressions.It is based on a publicly available dataset for emotion recognition that includes socio-demographic information and psychiatric profiles of individuals with mental illnesses.The study aims to explore how effectively these models can identify and classify emotions based on facial cues, considering the diverse psychiatric backgrounds of the subjects.It also aims to investigate to what extent the severity of the psychiatric condition affects the level of certainty of the predictions.