Seizure detection on/off system using rats' ECoG.
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.
Laboratory for Restorative Neurotechnology, Brown University, Providence, RI 02912, USA. yun_sang_park@brown.edu
Yun S
YS
Park
Theoden I
TI
Netoff
Xiaofeng
X
Yang
Keshab K
KK
Parhi
D000465:Algorithms; D000818:Animals; D001921:Brain / Q000503:physiopathology*; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D008297:Male; D010363:Pattern Recognition, Automated / Q000379:methods*; D051381:Rats; D017207:Rats, Sprague-Dawley; D015203:Reproducibility of Results; D012640:Seizures / Q000175:diagnosis* / Q000503:physiopathology*; D012680:Sensitivity and Specificity