NeuroTune

Inspiration

We were inspired due to the fact the we’re all students that use music when we study, and we wanted to know how we can use our brain readings to help change our mood.

What it does

It takes in EEG readings and based on the reading recommends music from your Spotify data to help change moods

How we built it

We used Python as our primary language, and we used the DREAMER dataset to train and validate the model. After that, we made three algorithms that worked on the EEG readings, classifying the emotions, and using song recommendations from Spotify data

Challenges we ran into

The main challenges we ran into is implementing the dataset from the .mat files, and working the Muse headband for the demo

Accomplishments that we're proud of

We were really proud of the program working as intended

What we learned

We learned how to use machine learning models for classification, using APIs to interact with everyday apps, and implementing technology like Muse to test our model