Facial Expression Evaluation to assess mental health through Deep Learning


Prajwal Gaikwad, Sanskruti Pardeshi, Shreya Sawant, Shrushti Rudrawar, Ketaki Upare
Computer dept,AISSMS IOIT, Pune.


Expressions have been one of the most primary forms of non-verbal communication for humans. This is very natural and has formed an irreplaceable part of our lives. The facial expressions have also been highly useful parameters in the understanding of human behavior and analysis of the human psyche. The psychotherapists have been engaged in this practice for a long time and the rise of awareness about mental health issues have been leading to an increase in the number of patients. Therefore, there is a need for an accurate analysis tool for achieving the facial expression detection. To provide a solution to this problem, this research article illustrates a facial expression technique through the use of Feature Extraction along with Convolutional Neural Networks and Decision tree. The approach has been effectively evaluated for its accuracy which has resulted in highly satisfactory results.