MIT EECS — Levine Undergraduate Research and Innovation Scholar
Predicting Migraines via Mobile- Focused Data Collection
Migraine attacks affect between 12- 16% of the American population, and can be extremely debilitating. The exact triggers for a migraine attack vary from person to person and might vary from one attack to another. This project seeks to better understand the triggers for a migraine attack, to provide migraine sufferers with a tool to track their migraines and, possibly even, to predict the next migraine attack before it happens. We aim to build a smartphone app that migraine sufferers can use to log their migraine attacks and that will collect physiologic data from the patient. This data will be used to explore the extent to which mathematical models may be developed to predict a migraine attack before it occurs. Additionally, by comparing data from different people, we aim to learn more about triggers that may be common among patients.
I’m thrilled to work at the intersection of computer science and the medical community. My passion for HCI and my experience as a mobile developer (both Android and iOS) has prepared me to build an information collecting app with a seamless user experience. I’m excited to learn more about machine learning and how it can help predict future migraines!