A robust spike and wave algorithm for detecting seizures in a genetic absence seizure model.
Animal Models are used extensively in basic epilepsy research. In many studies, there is a need to accurately score and quantify all epileptic spike and wave discharges (SWDs) as captured by electroencephalographic (EEG) recordings. Manual scoring of long term EEG recordings is a time-consuming and tedious task that requires inordinate amount of time of laboratory personnel and an experienced electroencephalographer. In this paper, we adapt a SWD detection algorithm, originally proposed by the authors for absence (petit mal) seizure detection in humans, to detect SWDs appearing in EEG recordings of Fischer 334 rats. The algorithm is robust with respect to the threshold parameters. Results are compared to manual scoring and the effect of different threshold parameters is discussed.
Xanthopoulos
Petros
P
Industrial and Systems Engineering Department at University of Florida, Gainesville, FL 32611, USA. petro.xanthopoulos@gmail.com
Liu
Chang-Chia
CC
Zhang
Jicong
J
Miller
Eric R
ER
Nair
S P
SP
Uthman
Basim M
BM
Kelly
Kevin
K
Pardalos
Panos M
PM
D000465:Algorithms; D000818:Animals; D001698:Biomedical Engineering / Q000379:methods; D001931:Brain Mapping / Q000379:methods; D004566:Electrodes; D004569:Electroencephalography / Q000379:methods; D004827:Epilepsy / Q000175:diagnosis; D004832:Epilepsy, Absence / Q000235:genetics* / Q000503:physiopathology*; D005583:Fourier Analysis; D051381:Rats; D011916:Rats, Inbred F344; D012640:Seizures; D012815:Signal Processing, Computer-Assisted; D012984:Software