EEG Emotion Classifier

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  After writing confusion matrix

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  Before writing confusion matrix

Inspiration

I was interested in studying how human emotions, specifically the alpha and gamma waves which are directly related to positive and negative emotions, are affected by recreational activities like praying, journalism, and relaxtion. In today's day and age, the average stress that anyone has to go through has increased significantly and this directly affects their mental health. After the passing of Rebecca "Becky" Blank, I wanted to analyze the effects of journaling specifically as I remember my first day where I met Becky on Bascom Hill who was handing out rice krispies and other treats. I actually wrote about this in a journal and this is where I started journaling.

What it does

It takes in data from a Kaggle data set involving the alpha and gamma brain wave data of people before and after writing journals. These brain waves signify whether the the emotions that are being felt at that very moment are positive or negative. The model than goes over this data and and classifies those emotions into positive, neutral and negative clusters and prints out a confusion matrix of the same for analysis.

How we built it

We used data from a Kaggle data set and trained a Machine Learning model to classify the predicted emotions. It takes in data from the data set and then classifies it into clusters for further analysis.

Challenges we ran into

Getting the accuracy of clustering high was hard due to the brain waves being in microvolts which is a very small change for an EEG sensor to pick up.

Accomplishments that we're proud of

The model successfully classifies positive and negative emotions and proves the point of the project which is to show that journaling is a good way to convert ones negative emotions into positive emotions.

What we learned

In today's day and age of high paced work, education, etc. people should take a second to look back and reflect on what bothers them. A simple task such as journaling one's experiences helps them feel a lot better and from the matrices, we see that before writing, the majority of the people had negative emotions and after writing, the majority of the people had positive emotions. The margin of error is small enough to successfully conclude that journaling is an effective way of improving one's mental health.

What's next for EEG Emotion Predictor

This research can be further utilized into creating an App which will allow for people to answer small journaling prompts and keep track of the same which will help them be more positive. The research will support the App's mission and foundation and they can further help train this model which will classify which prompts actually helped people feel better and this will be used to further improve the app.

Built With

• python