Interactive segmentation of EEG synchrony data in time-frequency space by means of region-growing and Bayesian regularization.
Electronics, Robotics and Automotive Mechanics Conference (2007)
Cuernavaca, Morelos, Mexico
Sept. 25, 2007 to Sept. 28, 2007
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CERMA.2007.82
Alfonso Alba , Universidad Autonoma de San Luis Potosi, Mexico
Edgar Arce , Universidad Autonoma de San Luis Potosi, Mexico
In this paper we present a new methodology for the interactive visualization and segmentation of electroencephalographic (EEG) scalp synchrony data. Synchrony measurements are estimated for all electrode pairs and classified as higher, lower, or equal than the baseline average. The classified values are then displayed in the form of Time-Frequency-Topography (TFT) maps, which can be segmented using a seeded region growing algorithm and a Bayesian regularization technique. Finally, we present the synchronization maps that result from the analysis of real EEG data from a figure categorization experiment.
E. Arce and A. Alba, "Interactive segmentation of EEG synchrony data in time-frequency space by means of region-growing and Bayesian regularization.," 2007 2nd Electronics, Robotics and Automotive Mechanics Conference(CERMA), Morelos, 2007, pp. 235-240.