A Comprehensive Node.js-Based Mental Health Monitoring and Exercise Recommendation System with AI-Driven Emotional Support
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| Format: | Recurso digital |
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Zenodo
2025
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| _version_ | 1866901603090432000 |
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| author | Abhilash T P, Avinash Kadappa Paragoudar, Darshan H G, Kalyani Sharath, Yuvaraj K B |
| author_facet | Abhilash T P, Avinash Kadappa Paragoudar, Darshan H G, Kalyani Sharath, Yuvaraj K B |
| contents | <div> <div>This paper presents a scalable backend system for mental health monitoring and fitness recommendation, built using Node.js, Express.js, and MongoDB. The system integrates secure user authentication, mood tracking, journaling, exercise recommendations based on age, and an AI-powered mental-health chatbot using OpenRouter’s GPT model. A fallback emotional-response engine ensures reliability even when external AI services fail. The architecture, modules, database structure, analytics engine, performance metrics, and system evaluation are discussed in detail. The system demonstrates strong potential for real-world deployment as part of digital well-being platforms.</div> </div> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17769662 |
| institution | Zenodo |
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| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A Comprehensive Node.js-Based Mental Health Monitoring and Exercise Recommendation System with AI-Driven Emotional Support Abhilash T P, Avinash Kadappa Paragoudar, Darshan H G, Kalyani Sharath, Yuvaraj K B <div> <div>This paper presents a scalable backend system for mental health monitoring and fitness recommendation, built using Node.js, Express.js, and MongoDB. The system integrates secure user authentication, mood tracking, journaling, exercise recommendations based on age, and an AI-powered mental-health chatbot using OpenRouter’s GPT model. A fallback emotional-response engine ensures reliability even when external AI services fail. The architecture, modules, database structure, analytics engine, performance metrics, and system evaluation are discussed in detail. The system demonstrates strong potential for real-world deployment as part of digital well-being platforms.</div> </div> |
| title | A Comprehensive Node.js-Based Mental Health Monitoring and Exercise Recommendation System with AI-Driven Emotional Support |
| url | https://doi.org/10.5281/zenodo.17769662 |