Laplacian Operator-Based Edge Detectors
IEEE Transactions on Pattern Analysis and Machine Intelligence
An experimental evaluation of ensemble methods for EEG signal classification
Pattern Recognition Letters
Epileptic seizure detection: A nonlinear viewpoint
Computer Methods and Programs in Biomedicine
Early detection of epileptic seizures based on parameter identification of neural mass model
Computers in Biology and Medicine
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Differential operators can detect significant changes in signals. This has been utilized to enhance the contrast of the seizure signatures in depth EEG or ECoG. We have actually taken normalized exponential of absolute value of single or double derivative of epileptic ECoG. This in short we call differential filtering. Windowed variance operation has been performed to automatically detect seizure onset on differentially filtered signal. A novel method for determining the duration of seizure has also been proposed. Since all operations take only linear time, the whole method is extremely fast. Seven empirical parameters have been introduced whose patient specific thresholding brings down the rate of false detection to a bare minimum. Results of implementation of the methods on the ECoG data of four epileptic patients have been reported with an ROC curve analysis. High value of the area under the ROC curve indicates excellent detection performance.