According to the CDC more than 795000 people in the United States have a stroke. About 610,000 of these are first or new strokes. Thus, we believe that we are solving a large-scale issue that affects both people in the US and globally. Our research group integrates patent-pending conductive silicone electrode technology embedded in a convenient and efficient earpiece to maximize neural signaling with machine learning to develop an innovative and minimally invasive diagnostic device (NIURA) to measure neural electrical activity. Using a modified electrocardiogram analog front-end device to ensure the two inputs were around mid rail potential, the device would be looking for electrical difference rather than heartbeats. With fast fourier transform, frequencies are identified from complex sine waves that include phase, amplitude, and frequency. The project has received IRB approval and is currently conducting trials on the product. By incorporating a machine learning algorithm, which is currently under development, the technology can serve as a diagnostic tool in detecting brain aneurysms and epilepsy that can detect mood as well. When the mood is detected by the user, they would be matched with a music playlist through our mobile app and listen to the playlist by using the earbuds. The user can then listen, edit, and share these playlists with the broad community. Hence, not only do our earbuds serve as a diagnostic tool for multiple neurological conditions, but we also aim to create a sense of community through music matching and listening around the world

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