Cross-correlation based μECoG waveform tracking.

Clinical electrodes for epileptic seizure monitoring traditionally require a tradeoff between coverage area and spatial resolution. However, with multiplexed, flexible array devices, high spatial resolution is possible over large surface areas. This high resolution data, recorded from 360 electrodes or more, is difficult to review manually for subtle patterns. Here we develop innovative methods for visualizing micro-electrocorticography (μECoG) datasets. The data contains seizure and non-seizure dynamics that can be used to better understand how seizures begin, progress, and end. Novel visualization techniques allow the researcher to better understand the data by arranging it in accessible ways. This paper presents tools to visualize a seizure waveform's velocity and location over a given window of time.

Duke Scholars

Author Jonathan Viventi Biomedical Engineering