We present an enhanced algorithm for seizure onset and offset detection in rats' ECoG. Because a seizure in rats' ECoG evolves much more stereotypically than that in human, analyzing seizure evolution in rats' ECoG is advantageous to understanding the evolution process. The proposed algorithm outperforms a prior automatic seizure detection and termination system in in-vivo rats' ECoG. We improve the algorithm by using relevant frequency bands of 14-22 Hz to onsets and 7-45 Hz to offsets; by using spectral power rather than spectral amplitudes for its feature; and by replacing the 2-point moving-average filter for postprocessing with a 2(nd) order Kalman filter. Not only does the proposed algorithm provide better detection statistics, but it lowers the system's complexity by no longer requiring computation of a fast Fourier transform and by using a single structure with the two different spectral power features for onset and offset detection.
|Number of pages
|Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
|Published - 2012
|34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012 → Sep 1 2012