Automated Seizure Detection Using Statistical Analysis of EEG Time-Domain Signals
Sherri Yifan Geng
Blair Student Finalists in National Intel Science Search
In this medicine and health entry, an automated detection system is created to identify seizure patterns in digital EEG (electroencephalograph) data. Two summers were spent at the
Walter Reed Army Institute of Research, working to automate the time-consuming manual process of scanning continuous EEG recordings. The solution - a computerized detection algorithm - also may be used to analyze other types of information, such as electrocardiogram data, and the researcher is applying for a patent.
Sherri Yifan Geng is one of Four Montgomery Blair High School students to become finalists in this year’s Intel Science Talent Search, out of 40 in all of the United States. This is the most finalists from any high school or school district in the nation. Born in China, Geng is an editor-in-chief of the school newspaper, co-president of the physics team and president of the science club. A published author and poet and an accomplished musician with perfect SAT scores, she has received numerous awards for academic achievements and top honors as a world-class table tennis player. Geng plans to study at Harvard.