DocumentCode
140089
Title
Cross-correlation based μECoG waveform tracking
Author
Schubert, Thomas ; Trumpis, M. ; Rivilis, Nicole ; Viventi, J.
Author_Institution
Dept. of Electr. & Comput. Eng., New York Univ., New York, NY, USA
fYear
2014
fDate
26-30 Aug. 2014
Firstpage
3264
Lastpage
3267
Abstract
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.
Keywords
bioelectric potentials; biomedical electrodes; data visualisation; electroencephalography; medical disorders; medical signal processing; neurophysiology; tracking; clinical electrodes; cross-correlation based μECoG waveform tracking; epileptic seizure monitoring; flexible array devices; microelectrocorticography dataset visualization; multiplexed array devices; seizure waveform location visualization; seizure waveform velocity visualization; spatial resolution; Arrays; Band-pass filters; Correlation; Data visualization; Electrodes; Epilepsy; Spatial resolution; μECoG; Data Visualization; ECoG; micro-electrocorticography;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE
Conference_Location
Chicago, IL
ISSN
1557-170X
Type
conf
DOI
10.1109/EMBC.2014.6944319
Filename
6944319
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