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Research Article

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

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  • @ARTICLE{10.4108/eetpht.10.5328,
        author={Sanjana Bhat and Reeja S R},
        title={A Comprehensive Study on Mental Illness Through Speech and EEG Using Artificial Intelligence},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={10},
        number={1},
        publisher={EAI},
        journal_a={PHAT},
        year={2024},
        month={3},
        keywords={Artificial Neural Network, Mental Illness, Facial Expressions},
        doi={10.4108/eetpht.10.5328}
    }
    
  • Sanjana Bhat
    Reeja S R
    Year: 2024
    A Comprehensive Study on Mental Illness Through Speech and EEG Using Artificial Intelligence
    PHAT
    EAI
    DOI: 10.4108/eetpht.10.5328
Sanjana Bhat1,*, Reeja S R1
  • 1: Vellore Institute of Technology University
*Contact email: sanjana.21bce8094@vitapstudent.ac.in

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.

Keywords
Artificial Neural Network, Mental Illness, Facial Expressions
Received
2023-12-10
Accepted
2024-03-01
Published
2024-03-07
Publisher
EAI
http://dx.doi.org/10.4108/eetpht.10.5328

Copyright © 2024 S. Bhat et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.

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