International Journal For Multidisciplinary Research

E-ISSN: 2582-2160     Impact Factor: 9.24

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 1 (January-February 2025) Submit your research before last 3 days of February to publish your research paper in the issue of January-February.

A study on AI driven mental health monitoring system

Author(s) Ravi Singh, Mansi Yadav, Ayushi Saini
Country India
Abstract Mental health challenges have become a global concern, with millions affected by conditions such as depression, anxiety, and stress. Despite the growing need for mental health services, barriers such as stigma, limited accessibility to care, and a shortage of trained professionals hinder timely interventions. The integration of artificial intelligence (AI) into mental health monitoring systems offers a transformative approach to addressing these challenges.

AI-driven systems leverage machine learning algorithms, natural language processing (NLP), and data analytics to monitor and assess mental health in real time. These systems can analyze diverse data sources, including speech patterns, text inputs, facial expressions, and physiological signals, to identify early signs of mental health issues. By providing continuous, scalable, and non-invasive monitoring, AI enhances traditional methods by offering personalized insights and timely interventions.

Recent advancements in AI, such as deep learning and emotion recognition, have significantly improved the accuracy and reliability of these systems. Moreover, the incorporation of wearable technology and mobile health applications enables individuals to track their mental well-being seamlessly. While promising, these systems also raise ethical concerns around privacy, bias, and the need for robust validation in clinical settings.

This paper explores the design, implementation, and ethical considerations of AI-driven mental health monitoring systems, highlighting their potential to revolutionize mental health care and improve patient outcomes.
Keywords Depression detection, Stress management, Multimodal data integration, Machine learning algorithms, Sentiment analysis, Physiological metrics, Real-time monitoring, Ethical considerations in AI
Field Computer Applications
Published In Volume 7, Issue 1, January-February 2025
Published On 2025-01-26
Cite This A study on AI driven mental health monitoring system - Ravi Singh, Mansi Yadav, Ayushi Saini - IJFMR Volume 7, Issue 1, January-February 2025. DOI 10.36948/ijfmr.2025.v07i01.35707
DOI https://doi.org/10.36948/ijfmr.2025.v07i01.35707
Short DOI https://doi.org/g829rt

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