MENTAL HEALTH TRACKER AND SUPPORT SYSTEM

Mental health has become a growing concern in today’s fast-paced and stressful world, where individuals often struggle to track and manage their emotional well-being. To address this challenge, this project presents an AI-Based Mental Health Tracking and Support System that helps users monitor, reflect, and improve their mental wellness through intelligent mood analysis and self-care tracking. The system enables users to record daily moods, journal entries, affirmations, goals, and gratitude reflections, creating a comprehensive emotional profile over time. Developed using Python and Streamlit, it provides an interactive dashboard where users can visualize emotional trends, view history, and track progress through engaging data charts. All user inputs are securely stored in a SQLite database, ensuring persistence and easy retrieval. The system promotes self-awareness, consistency, and emotional balance by offering structured journaling and progress insights. By integrating automation, visualization, and data-driven reflection, this project aims to support mental wellness in an accessible, private, and user-friendly way.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-01-22
DOI
https://doi.org/10.5281/zenodo.18333643
Primary Topic
Mental Health via Writing
Type
article
Field-Weighted Citation Impact
0.00
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article

MENTAL HEALTH TRACKER AND SUPPORT SYSTEM

R.Pushpakumari, N.Mahmuthal
Zenodo (CERN European Organization for Nuclear Research)
Mental Health via Writing
article

MENTAL HEALTH TRACKER AND SUPPORT SYSTEM

R.Pushpakumari, N.Mahmuthal
article en

Abstract

Mental health has become a growing concern in today’s fast-paced and stressful world, where individuals often struggle to track and manage their emotional well-being. To address this challenge, this project presents an AI-Based Mental Health Tracking and Support System that helps users monitor, reflect, and improve their mental wellness through intelligent mood analysis and self-care tracking. The system enables users to record daily moods, journal entries, affirmations, goals, and gratitude reflections, creating a comprehensive emotional profile over time. Developed using Python and Streamlit, it provides an interactive dashboard where users can visualize emotional trends, view history, and track progress through engaging data charts. All user inputs are securely stored in a SQLite database, ensuring persistence and easy retrieval. The system promotes self-awareness, consistency, and emotional balance by offering structured journaling and progress insights. By integrating automation, visualization, and data-driven reflection, this project aims to support mental wellness in an accessible, private, and user-friendly way.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 85%
Mental Health via Writing
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MENTAL HEALTH TRACKER AND SUPPORT SYSTEM — R.Pushpakumari, N.Mahmuthal · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS