Team 437_HealthPal

A conversation with our chatbot
It takes the necessary steps when the situation gets severe
End session pop-up
Check-in questionnaire after ending the session, linked to the rewards system

Inspiration

The inspiration for HealthPal came from recognizing the growing need for accessible mental health support, especially for young Indians who may often face challenges and emotions they need to talk about. We aimed to bridge the gap between individuals seeking mental health assistance and the limited availability of therapists. A user-friendly website with a chatbot seemed like an innovative solution to provide immediate support and resources to anyone in need.

What it does

HealthPal is a website that hosts a mental health chatbot, offering personalized support, resources, and guidance to users. The chatbot engages users in meaningful conversations, and provides emotional support and strategies. It can assess users' mental health status, and connect users to crisis support if necessary. At the end of each session, a pop-up questionnaire helps the user assess their mood and daily activities based on which they earn stars, adding to their rewards.

How we built it

To build HealthPal, we used a combination of frontend and backend technologies. The frontend was developed using HTML, CSS, JavaScript and Bootstrap to create a responsive user interface. For the chatbot's logic, we deployed the Sequential model using Python's Keras library consisting of 3 layers. The training data for the neural network was created by pre-processing the data originally in a JSON format. Natural Language Processing techniques such as tokenization, lemmatization and one-hot encoding & decoding were used to transform our data into the appropriate input for our model. The backend was built using Python and Flask to handle user interactions, process data, and communicate with the chatbot.

Challenges we ran into

During the development process, we faced challenges in fine-tuning the chatbot's natural language processing capabilities to provide accurate responses and empathetic interactions. Some libraries and modules implemented in the Google Colaboratory environment also posed challenges when we executed them in a virtual environment. Integrating the machine learning model and ensuring smooth communication between frontend and backend components also presented some hurdles. As a team we had diverse opinions on how the website should look and feel.

Accomplishments that we're proud of

We could work together as a team and complete the project in the stipulated amount of time. Each individual member has pushed their limits and worked hard for each part of the project. The hackathon helped us to work in collaboration and considering everyone's opinion and taking constructive criticism. We got out of our comfort zones and used technologies we have not used before.

What we learned

Teamwork: We learned to collaborate effectively as a team in order to achieve our goals and to accept constructive feedback from each other to help us grow. We all contributed individually in the project and we were able to merge it all together.
Problem Solving: We were motivated to find the best solution and think critically, creatively, and outside the box to address the problem.
Coding Skills: Our technical skills have significantly improved due to this hackathon. We were able to hone our proficiency in the Python programming language, and gain hands-on experience with new technologies.
Time Management: With the limited time frame, we had to prioritize and delegate all the tasks for our project. It ensured we were focused throughout and learned to use our time wisely.

What's next for Team 437_HealthPal

Moving forward, we aim to enhance the chatbot's capabilities by continuously refining its algorithms and incorporating feedback from users and mental health experts. Key points:

Personalization: The chatbot will take into account factors such as the user's personal history, hence creating more personalized interactions with the user, while also providing usage analytics.
Security: Implementation of secure user authentication mechanisms would ensure that only authorized users can access the chatbot and their personal information.
Progress Tracking: A visual progress tracker will showcase the user's advancement in their mental health goals which helps user to track their progress, celebrate milestone and stay motivated on their mental health journey.