Improving the Signal to Noise Ratio of Event-Related EEG Signals in High Risk Newborns
An integral component of the understanding and processing of a signal lies in our ability to successfully separate the desired signal from any inherent noise. In some situations, specifically those with a weak signal or a large amount of noise, the signal-to-noise ratio (SNR) makes this process challenging. This project focuses on investigating methods to increase the SNR in processes that involve multiple measurements of brain activity, with measurements being completed simultaneously or in multiple trials over time.
Research Focus
Our expectation is that this method will be applicable to a variety of disciplines, ranging from astrophysics, for processing signals from radio telescope arrays, to biomedical applications, including interpreting EEG and other physiological data. The primary combining method we plan to pursue is a weighted average of the signals. Our goal is to find the optimum coefficients to minimize the estimation error.