Title :
Comparison of temporal variability of epileptic ECoG signals
Author :
Janjarasjitt, Suparerk ; Loparo, Kenneth A.
Author_Institution :
Dept. of Electr. & Electron. Eng., Ubon Ratchathani Univ., Ubon Ratchathani, Thailand
Abstract :
Temporal characteristics of the EEG have been extensively studied for their relationship to both sleep and epilepsy. In this work, a new computational algorithm for quantifying the temporal variability of signal is proposed. The proposed computational algorithm is based on local minima and local maxima. The temporal variability of ECoG data obtained from epilepsy patients corresponding to different pathological brain states, i.e., during a non-seizure period and during an epileptic seizure activity, is examined. From the computational results, it can be observed that there are significant differences of both features between epileptic ECoG data during a non-seizure period and during an epileptic seizure activity.
Keywords :
bioelectric phenomena; diseases; electroencephalography; medical signal processing; EEG temporal characteristics; epilepsy patients; epileptic ECoG signal temporal variability; local maxima; local minima; pathological brain states; sleep; Complexity theory; Electroencephalography; Epilepsy; Fractals; Pathology; Sleep; Time series analysis; electrocorticography; epilepsy; local minmax; seizure; variability;
Conference_Titel :
Electronics and Information Engineering (ICEIE), 2010 International Conference On
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-7679-4
Electronic_ISBN :
978-1-4244-7681-7
DOI :
10.1109/ICEIE.2010.5559777