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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65372
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Engineering
Sinhgad Institute of Technology and Science, Pune
Computer Engineering
Sinhgad Institute of Technology and Science, Pune
Computer Engineering
Sinhgad Institute of Technology and Science, Pune
Computer Engineering
Sinhgad Institute of Technology and Science, Pune
Computer Engineering
Sinhgad Institute of Technology and Science, Pune
Mental health issues like stress, anxiety and depression are becoming more common around the world. This means we need to find ways to make Mental Health Support Systems more accessible and available when people need them. This research is about creating a Mental Health Management System that uses Artificial Intelligence to help people with their health. The Mental Health Management System uses Artificial Intelligence and other techniques like Natural Language Processing and Emotion Recognition to give people the support they need and to check for mental health issues early on. The Mental Health Management System looks at how people interact through text, speech and facial expressions to figure out how they are feeling. If they are having any psychological problems. The system uses different models like Convolutional Neural Networks and Natural Language Processing models to recognize emotions more accurately. A chatbot is used to talk to people and give them advice on how to take care of their well-being based on how they are feeling. The Mental Health Management System also keeps track of peoples emotions in a way and makes reports while making sure to follow the rules and keep everything private. By looking at different ways to recognize emotions the Mental Health Management System is better than older systems that only looked at one thing. The Mental Health Management System helps people take care of their emotions and finds health issues early on. The Mental Health Management System is also a way to give people the help they need to take care of their mental health over time. Studies have shown that using different ways to recognize emotions with Artificial Intelligence can really help people, with their mental health.
KEYWORDS
The Mental Health Management System that uses Artificial Intelligence is a way to keep an eye on our mental health and get support when we need it. This system uses Artificial Intelligence and other things like Natural Language Processing and Speech Emotion Recognition to figure out how people are feeling. It looks at lots of things to understand peoples emotions better than ways of doing it. The chatbot that uses Artificial Intelligence gives people advice and support to help them feel better. The Mental Health Management System can find out if someone is stressed or anxious or depressed early on so they can get help right away. The system keeps all the information safe and private. This solution helps people get health support when they need it which is a big problem. Students and people who work and healthcare organizations can all use the Mental Health Management System. Maybe one day the Mental Health Management System will be able to connect to devices that people wear and talk to people in different languages and use even better Artificial Intelligence. The Mental Health Management System shows that Artificial Intelligence can really help people with their health and feel better. The Mental Health Management System is a thing, for peoples mental health.
[1] Livingstone, S. R., and Russo, F. A. (2018). ‘”The Ryerson Audio- Visual Database of Emotional Speech and Song (RAVDESS).” PLOS ONE, 13(5): e0196391. ” [2] Rashkin, H., Smith, E. M., Li, M., and Boureau, Y. L. (2019). “ ”Towards Empathetic Open-domain Conversation Models: A New Benchmark and Dataset.” Proceedings of ACL 2019. ” [3] Nair, R., and Soni, M. (2023). “ ”Speech Emotion Recognition for Mental Health Monitoring using CNN and SVM Models.” International Journal of Machine Learning and AI, 12(3), 45–52.” [4] Dosovitskiy, A., Beyer, L., Kolesnikov, A., Weissenborn, D., et al.(2021). “ ”An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.” International Conference on Learning Representations (ICLR). ” [5] Ahmed, F., and Khan, S. (2022). ‘ ”Vision Transformers for Facial Emotion Recognition.” IEEE Access, 10, 10231–10241.. [6] Fitzpatrick, K. K., Darcy, A., and Vierhile, M. (2017). “ ”Delivering Cognitive Behavioral Therapy to Young Adults with Depression Using a Conversational Agent (Woebot).” JMIR Mental Health.
Publication Date
6/23/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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