A Comprehensive Study on Mental Illness Through Speech and EEG Using Artificial Intelligence

Sanjana Bhat; Reeja S R

doi:10.4108/eetpht.10.5328

Authors

Sanjana Bhat Vellore Institute of Technology University
Reeja S R Vellore Institute of Technology University

DOI:

https://doi.org/10.4108/eetpht.10.5328

Keywords:

Artificial Neural Network, Mental Illness, Facial Expressions

Abstract

A typical mental ailment is depression that considerably harms an individual's everyday activities as well as their mental health. In light of the fact that mental health is one of the biggest problems facing society, researchers have been looking into several strategies for efficiently identifying depression. Mental illness can now be identified through speech analysis thanks to modern artificial intelligence. The speech aids in classifying a patient's mental health status, which could benefit their new study. For the purpose of identifying depression or any other emotion or mood in an individual, a number of past studies based on machine learning and artificial intelligence are being studied. The study also examines the effectiveness of facial expression, photos, emotional chatbots, and texts in identifying a person's emotions. Naive-Bayes, Support Vector Machines (SVM), Linear Support Vectors, Logistic Regression, etc. are ML approaches from text processing. Artificial Neural Network (ANN) is a sort of artificial intelligence method used to extract information from photos and classify them in order to recognise emotions from facial expressions.

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