Convolution neural network based facial expression and gender recognition approach for monitoring mental health in a real time environment

Abstract

Mental health disturbances exert a profound influence on an individual s physical wellbeing, newlineas is apparent in numerous medical scenarios, including those involving stroke, newlinepostpartum complications, and cancer. When these disturbances are left unattended, they newlinecan precipitate adverse outcomes such as post-stroke depression, mental instability, and, newlinein extreme cases, suicidal tendencies. Consequently, it becomes imperative to institute newlineclose monitoring protocols for patients grappling with these challenges. Furthermore, newlinethe availability of comprehensive data about patients affective states equips healthcare newlinepersonnel with a heightened ability to assess and understand patient behavior. In this newlinecontext, facial expressions, a remarkably effective medium of non-verbal communication, newlineemerge as a valuable resource, affording insights into emotional states, mindset, and newlineunderlying intentions.