Title :
Comparison of predictability of epileptic seizures by a linear and a nonlinear method
Author :
McSharry, Patrick E. ; Smith, Leonard A. ; Tarassenko, Lionel
Author_Institution :
Dept. of Eng. Sci., Univ. of Oxford, UK
fDate :
5/1/2003 12:00:00 AM
Abstract :
The performance of traditional linear (variance based) methods for the identification and prediction of epileptic seizures are contrasted with "modern" methods from nonlinear time series analysis. We note several flaws of design in demonstrations claiming to establish the efficacy of nonlinear techniques; in particular, we examine published evidence for precursor identification. We perform null hypothesis tests using relevant surrogate data to demonstrate that decreases in the correlation density prior to and during seizure may simply reflect increases in the variance.
Keywords :
brain models; correlation methods; diseases; electroencephalography; medical signal detection; neurophysiology; prediction theory; time series; correlation density; epileptic seizure predictability; linear method; nonlinear method; nonlinear time series analysis; null hypothesis tests; precursor identification; surrogate data; traditional linear methods; variance based methods; Analysis of variance; Electrodes; Electroencephalography; Epilepsy; Magnetic recording; Performance analysis; Robustness; Signal processing; Statistics; Time series analysis; Algorithms; Brain; Computer Simulation; Electrodes, Implanted; Electroencephalography; Epilepsy, Temporal Lobe; False Positive Reactions; Humans; Linear Models; Models, Neurological; Nonlinear Dynamics; Quality Control; Reproducibility of Results; Sclerosis; Seizures; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Statistics as Topic;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2003.810688