Mind.me

• 

  Introduction

• 

  Zepp. Snippet of code in js to take heart rate.

• 

  web page. It displays daily data about your emotional status, with suggestions and integrations generated by GPT model

• 

  Scheme. The data is taken from the Zapp watch and sent to the database. The audio file will be elaborated with Hume API and resent back.

• 

  Mind.me. The sponsors' technologies we used.

• 

  gpt model

• 

  hume api

• 

  promt for GenAI

• 

  mysql database (data for predictions)

• 

  Tools used

• 

  Thanks

Inspiration

With Mind.me, emotions are finally on your side. In today’s fast-paced world, mental health often takes a backseat. However, it’s crucial to remember that our emotional well-being is just as important as our physical health. The inspiration behind Mind.me is the understanding that managing mental health should be a priority, not an afterthought.

What it does

Mind.me is an innovative system designed to enhance users' emotional awareness and empower them to manage their emotional well-being effectively. It operates seamlessly in the background, collecting data from various sources like heart rate, blood pressure, and voice recordings. This data is analyzed to track your mood throughout the day and uncover trends and patterns. The insights gained are then used to generate personalized, detailed suggestions and advice to help you manage your emotions better.

How we built it

Mind.me is a comprehensive system that includes a front-end application built using the Zepp Framework and a user-exclusive webpage. The webpage provides detailed explanations of the user's emotional status, refined prompts, and trends and graphs for understanding their long-term emotional trajectory.

The system leverages MindsDB for swift integration of the MySQL database in the backend and machine learning models. It utilizes GPT3.5 Turbo to construct human-like, detailed suggestions. The system uses a total of 57 predictors, including health data captured through the Zepp Watch sensors and emotions mapped throughout the day via the user's voice and discourse.

To convert voice into emotions, Mind.me employs Hume API, which uses state-of-the-art deep learning models specifically designed for this purpose. All data is stored in a MySQL database in the backend for optimal performance.

What's next for Mind.me

While Mind.me has already many features to help users manage their emotional well-being, there's still a long way to go. This application has the potential to change the lives of millions of people around the world. Future development will focus on improvements through third-party integrations and more complex data analytics.

Built With

• google-cloud
• hume-api
• javascript
• mindsdb
• mysql
• openai-api
• python
• react
• sql
• zepp