Inspiration

The drive to HackFSU was tiring already... now thirty hours of sleep deprivation later, the drive back will be extremely dangerous. We realized we can do something to stop this and save lives!

What it does

The Muse headband will read your mind! Signs of dozing off are easily revealed by your brain activity, and so an audio queue is sent directly to your phone to ensure alertness.

How we built it

The backbone of our application relies on typical Android Studio development mixed with introductory code provided by Muse for developers. After intensive testing and analyzing the typical patterns of the Alpha, Beta, Theta, Delta, and Gamma waves, we were able to arrive at consistent predictions to verify signs of drowsiness, daydreaming, and sleeping states of mind. We retrieved this data in the form of Muse files and made algorithms that could predict if someone is on the verge of falling asleep or is dangerously close to just not paying attention at all. We then implemented all of this information in Android Studio and developed an application that can take advantage of the information in order to keep you safe.

Challenges we ran into

We have never worked with Muse ever. We have never learned anything about frequency waves and their meanings before this. These were the biggest challenges to overcome since we were dipping our feet into something untouched; yet, we committed to see it through. We also had to be able to gather this new data, understand it, and utilize it in a short period of time.

Accomplishments that we're proud of

In the short time span that a typical Hackathon presents, we were not only able to tackle a task that we have never even touched, we were also able to properly collaborate with each other in order to bring a functioning application that implemented cutting edge technology. We know this can be eventually used to help save lives and it just fuels further purpose to our project.

What we learned

The team learned the basics of using and implementing the three basic Muse developer software consisting of Muse-IO, MuseLab, and MusePlayer; the basics of Android Studio; and their possible combined implementations.

What's next for Never-Muse-Focus

Hopefully, we can further advance this app to be more useful in realistic scenarios by providing machine learning so it becomes even more fine tuned in its decision-making depending on its user. This will increase it's accuracy to a higher degree and be of further use.

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