C.H.I.K.I.T.S.A

Cognitive Health Intelligence Knowledge with Keen Interactive Treatment Support from AI

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Overview

C.H.I.K.I.T.S.A is an advanced AI-powered mental health assistant designed to help individuals on their journey to better mental well-being. It integrates state-of-the-art technologies like emotion detection, real-time facial analysis, medical image analysis, and voice interaction. It provides personalized recommendations, mental health assessments, and emotional support while ensuring a user-friendly interface and robust data security.

⚠️ Disclaimer: C.H.I.K.I.T.S.A does not replace professional medical advice, diagnoses, or treatment.

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Features

Core Functionalities:

1. Mental Health Assessment:
   Personalized assessments and recommendations based on user inputs and interactions.

2. Emotion and Attention Detection:
   Uses webcam-based facial emotion analysis to detect emotional states and attention levels in real-time.

3. Voice Assistant Integration:
   A natural and engaging voice assistant to communicate with users effectively.

4. Medical Image Analysis:
   A feature for analyzing medical images to detect potential conditions and reduce user stress.

5. Feedback Mechanism:
   Displays user-specific feedback with/without login. Login-based feedback now includes user names for personalization.

6. Open-Ended and Close-Ended Questions:
   Tailored questionnaires to understand user needs and mental states.

7. Enhanced User Experience:
   Updated CSS themes and new instructions on the home page (home.png) for better usability.

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Future Roadmap:

1. Recommendation System:
   Recommend activities like breathing exercises or meditations based on user feedback and emotional states.

2. Stress Relief Modules:
   Add guided stress-relief exercises like breathing techniques and meditation.

3. Expanded Question Bank:
   Include more detailed mental health evaluation questions for better insights.

4. Advanced Recommendations:
   Tailor recommendations based on the user's detected emotions or mental health assessment.

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Updated Architecture

Flow Diagram:

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Installation

Steps to Set Up the Project:

1. Clone the Repository:

   git clone https://github.com/vinayak1729-web/chikitsa_main_ai

2. Install Dependencies:

   pip install -r requirement.txt

3. Run the Application:

   python app.py

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How to Use

1. Login:
   Log in to personalize your experience.

2. Access Features:

   • For mental health assessments, select from open-ended or close-ended questionnaires.
   • To interact, use the chatbot or voice assistant.
   • Webcam integration allows for real-time emotion and attention detection.

3. Get Feedback:
   After assessments, view feedback with personalized recommendations. Logged-in users will see their names in the feedback section.

4. Image Analysis:
   Upload medical images for stress-reducing insights.

5. Explore Stress Relief:
   (Coming Soon) Access guided exercises for stress relief and relaxation.

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Screenshots

Updated Screens

• Home with Instructions
  

• Login Page
  

• Open-Ended Questions
  

• Close-Ended Questions
  

• Feedback (Logged-In)
  

• Feedback (Without Login)
  

• Voice Assistant
  

• Chatbot
  

• Image Analysis
  

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Challenges and Solutions

Updated Challenges:

1. Emotion and Attention Detection:

   • Problem: Implementing webcam-based facial analysis for real-time emotion detection.
   • Solution: Leveraged OpenCV and fine-tuned models to enhance accuracy and responsiveness.

2. Feedback Personalization:

   • Problem: Displaying personalized feedback based on user login state.
   • Solution: Integrated dynamic feedback rendering with user-specific data.

3. Voice Assistant Enhancements:

   • Problem: Aligning emotion detection with natural language responses.
   • Solution: Synced detected emotions with the assistant’s tone and response.

4. CSS and UI Design:

   • Problem: Improving user interface themes for accessibility.
   • Solution: Upgraded CSS themes, added instructions (home.png), and ensured responsive design.

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Contributing

Contributions are welcome!

Steps to Contribute:

1. Fork the Repository:

   git fork https://github.com/vinayak1729-web/chikitsa_ai

2. Create Your Feature Branch:

   git checkout -b feature/AmazingFeature

3. Commit Your Changes:

   git commit -m 'Add some AmazingFeature'

4. Push to the Branch:

   git push origin feature/AmazingFeature

5. Open a Pull Request:

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License

This project is licensed under the MIT License - see the LICENSE file for details.