EMOTION RECOGNITION FOR MENTAL HEALTH PREDICTION USING AI TECHNIQUES: AN OVERVIEW

Human facial expressions are a mirror of human thoughts, feelings and human mental states. Facial Emotion Recognition (FER) can provide a social advantage. It's like a form of silent communication. Emotion recognition technology will help to automatically detect the patient's emotions duri...

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Bibliographic Details
Published in:International journal of advanced research in computer science 2023-06, Vol.14 (3), p.87-107
Main Author: Singh, Sonali
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Emotion recognition
Emotional factors
Emotions
Face recognition
Feature extraction
Mental disorders
Mental health
Mental health care
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Summary:Human facial expressions are a mirror of human thoughts, feelings and human mental states. Facial Emotion Recognition (FER) can provide a social advantage. It's like a form of silent communication. Emotion recognition technology will help to automatically detect the patient's emotions during illness and avoid external acts such as suicide, mental disorders or mental health problems. If we understand all the signs of emotions, we can solve many problems for human beings. Emotion recognition and detection is also useful for healthcare. Through emotional state recognition, we can get information about patients. Recognizing a patient's emotions for a specific disease using artificial intelligence techniques is a challenging task. This article presents recognition, detection and methods for mental health patients. Using artificial intelligence techniques with an emotion detection library and matching emotions to mental health. This article uses an emotional scale to show that there is a link between negative emotions and mental health problems. In this paper, she provided a comprehensive review of AI-based FER methodology, including datasets, feature extraction techniques, algorithms, and recent breakthroughs with their applications in facial expression recognition. In the future, all aspects of FER for different ages would significantly influence the health research community.
ISSN:0976-5697
0976-5697
DOI:10.26483/ijarcs.v14i3.6975