Research has shown that closed-loop neurofeedback algorithms that play sounds in sync with brainwaves, particularly during the up states of slow oscillations (SO) of slow wave sleep (SWS), can improve sleep quality and enhance memory. However, long-term studies, especially on older adults with fragmented sleep and reduced SWS, are limited by lab settings. Conducting studies in-home would address this, but many consumer EEG headbands lack flexibility for testing custom algorithms. This project focuses on creating a user-friendly, portable EEG system capable of integrating our lab’s neural network-based algorithms, with the goal of allowing long-term, at-home studies. Success in this project will make sleep research more accessible and provide flexibility for testing novel algorithms for sleep neuromodulation.

My motivation for pursuing this project stems from the opportunity to apply my studies in electrical engineering and computer science to a more interdisciplinary setting that I’ve gained an interest in recently. Both sleep and the brain are fascinating subjects we still have a lot to learn about, and I’m more than excited to provide contributions to their study. As I consider my next steps, I hope that this year-long research project will provide guidance in my decision of whether to continue to graduate school and what my possible focus might be.