AI-driven emotion recognition systems for sustainable mental health care: an engineering perspective

Title

AI-driven emotion recognition systems for sustainable mental health care: an engineering perspective

Creator

Ahmad, Akram; Singh, Vaishali; Upreti, Kamal

Description

Emotion recognition systems are transforming human-computer interaction (HCI) applications by enabling AI-driven, adaptive, and responsive mental health interventions. This study explores AI-based emotion recognition technologies using facial expressions, voice analysis, text-based sentiment processing, and physiological signals to develop scalable, real-time mental health support systems. Utilizing datasets such as FER2013, JAFFE, and CK+, our research examines deep learning models, including EfficientNet-XGBoost, which achieved over 90% accuracy across key evaluation metrics. Unlike traditional mental health interventions, AI-driven systems provide cost-effective, accessible, and sustainable solutions through telemedicine, wearable biosensors, and virtual counselors. The study also highlights critical challenges such as algorithmic bias, ethical AI compliance, and the energy consumption of deep learning models. By integrating machine learning, cloud-based deployment, and edge computing, this research contributes to the development of sustainable, ethical, and user-centric AI solutions for mental health care. Future directions include AI model optimization for energy-efficient deployments and the creation of diverse, inclusive datasets to improve performance across global populations. 2025, Intelektual Pustaka Media Utama. All rights reserved.

Source

International Journal of Advances in Applied Sciences;Volume;14;Issue;4;pp.1111-1117

Date

01-01-2025

Publisher

Intelektual Pustaka Media Utama

Subject

Environmental awareness; Human-computer interaction; Machine learning; Mental illness; Predictive modeling; Sustainable engineering

Coverage

Ahmad A., Maharishi University of Information Technology, Lucknow, India; Singh V., Maharishi University of Information Technology, Lucknow, India; Upreti K., CHRIST (Deemed to be University), Delhi NCR Campus, Ghaziabad, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 22528814;

Format

online

Language

English

Type

Article

Identifier

https://doi.org/10.11591/ijaas.v14.i4.pp1111-1117

https://www.scopus.com/pages/publications/105026990261?origin=resultslist