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This is sign page and if user want to create a account then this is location
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profile section
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it is compalsory to fell basic question
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Chat section that user can interact and gather information about mental health and have user friendly behaviour
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this is the facial emotion tracking with help of faceapp.js it will able to detect the stress level on the basis of facial emotion
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Resource section in which user can explore all by itself
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This is therapist section nearby to you
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This is home page it can access without sign in user can explore some of feature
Inspiration
🔹 Mental health issues such as stress, anxiety, and emotional burnout are increasing. 🔹 Early symptoms often go unnoticed due to stigma and lack of tools. 🔹 Inspired to create a user-friendly, self-monitoring platform. 🔹 Goal: Early awareness through data-driven insights.
What it does
🔹 Allows users to input daily mood and emotional reflections. 🔹 Uses AI-based emotion and sentiment analysis. 🔹 Detects stress, anxiety, and emotional patterns. 🔹 Visualizes trends using interactive dashboards. 🔹 Helps users understand mental health over time
How we built it
🔹 Frontend: Simple, responsive web interface. 🔹 AI Engine: Pre-trained NLP models for emotion detection. 🔹 Data Storage: Secure storage of analyzed results. 🔹 Visualization: Tableau dashboards for insights and trends. 🔹 Integration: End-to-end flow from user input to analytics.
Challenges we ran into
🔹 Designing a solution that is technically accurate and emotionally sensitive. 🔹 Integrating AI analysis with Tableau dashboards. 🔹 Working within provisioned Tableau environment constraints. 🔹 Ensuring clarity, privacy, and usability.
Accomplishments that we're proud of
🔹 Built a complete end-to-end system. 🔹 Successfully combined AI + Web + Data Visualization. 🔹 Created a clean and accessible UI. 🔹 Delivered meaningful insights without complexity.
What we learned
🔹 Importance of responsible AI in sensitive domains. 🔹 How data visualization improves understanding. 🔹 Practical experience with AI model integration. 🔹 Better understanding of user-centric design.
What's next for AI-Driven Mental Health Monitoring & Analytics Platform
🔹 Voice-based emotion analysis 🔹 Personalized mental health recommendations 🔹 Real-time alerts for high-risk users 🔹 Role-based dashboards for counselors 🔹 Improved AI accuracy & data security
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