Our Goal

Growing up, it was always fascinating to watch Sci-Fi movies like The Matrix. It was incredible how people could break the wall between brain and machine, having them work as a cohesive unit. Wave.ly's goal is to do just that. With incredible rise in BCI (Brain-Computer Interface) devices over the last few years, many people are looking to invest their time and money into researching how these devices work and how they can analyze data more efficiently. With all the complicated hardware and software in the BCI industry right now, it's incredibly difficult for hobbyists and beginners to get started using BCI to develop their own understanding. That's why we made a streamlined system that allows people to implement them within their own personal devices. As the industry progresses, BCI's will become cheaper and more accessible to everyone, which is why we chose to invest ourselves in this incredible subject.

What Does It Do?

Wave.ly's main functionality is built around using a neural network that is trained to analyze specific patterns of the brain when you think about a certain action such as biting an apple, smelling a rose or pushing a box. When given enough data about a certain thought, Wave.ly's algorithm can start to pick up patterns about how your neurons fire when thinking about a certain action, being able to recognize the specific set of patterns when you start thinking about it. We can then use these specific actions to map to keybindings that you can use on your own computer.

How We Built It

Wave.ly was built using the Cortex API in python using websockets to interact with the API. The headset we used for the purpose of demoing this is the EMOTIV Insight.

Challenges We Faced

We ran into many challenges at the beginning of making this project. The main one being time. Given the complexity of the software, and having only 36 hours to make it, unfortunately we were not able to implement all of the features in our final UI build, one of which was the ability of emotion tracking (Stress, Excitement, Focus etc.). Some of the more complex mechanics of our project was the ability to move the mouse using a gyroscope and accelerometer on the BCI headset, which involved using quaternions to map mouse movements.

Accomplishments That We're Proud Of

We are incredibly proud of the progress that we made in 36 hours, as given the complexity of this project, we knew going into the hack-a-thon that this would be an incredibly ambitious project, but we were incredibly eager to get our idea out there. We're very impressed with our quick thinking and problem solving ability that , throughout the event there were many people who were very impressed with the design of our mechanisms and our idea. We are very proud of what we did in the time frame and are looking forward to pursuing with this idea in the future.

What We Learned

Throughout the hackathon we learned a lot about developing our skills, not just as engineers and developers, but as entrepreneurs and creative thinkers. We were given a lot of great advice about the implementation of our product by senior mentors and judges, as well as strategic approaches to solving problems. This really helped us as we cam all apply it in fields that we would like to pursue in the future.

What's Next for Wave.ly?

Given some more time to work on this project, we could definitely add a lot more functionality in terms of customizing the UI as well as add some of the features we missed out on, like the emotion tracking. Overall, we'd like to take the project out of testing and prototyping, and bring it to an accessible platform, that everyone can use.

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