Improved remote mental health illness assessment and detection using facial emotion detection and speech emotion detection

Abstract

The use of Artificial Intelligence in the healthcare sector has been recently observed. Projects are being made that integrate AI and therapeutic sessions[1]. A new area of study evolved where doctors, along with technicians, collaborate to create projects which will help give the old school therapy an advanced technical form. This study uses the original therapy techniques for mental health assessment and integrates it with machine learning models for facial emotion recognition and speech pattern recognition to get a better understanding of a patient’s mental health condition and help them deal with it. This project assists the patient in the diagnosis of 11 different mental health conditions where the patient’s emotional state is taken into consideration while diagnosis. Patients’ social interactions are also being checked and analyzed regularly. This project calculates a verdict which declares whether the patient suffers from the diagnosed illness or whether they should retake the tests. In addition, the project maintains records of the patient's emotional and mental health journey.