Predictability of epileptic seizures: a comparative study using Lyapunov exponent and entropy based measures
In this paper, a comparative study involving measures from the theory of chaos, namely the short-term largest Lyapunov exponent, Shannon and Kullback-Leibler entropies from information theory, has been carried out in terms of their predictability of temporal lobe epileptic seizures. These three measures are estimated from electroencephalographic (EEG) recordings with sub-dural and in-depth electrodes from various brain locations in patients with temporal lobe epilepsy. Techniques from optimization theory are applied to select optimal sets of electrodes whose dynamics is then followed over time. Results from analysis of multiple seizures in two epileptic patients with these measures are presented and compared in terms of their ability to identify pre-ictal dynamical entrainment well ahead of seizure onset time.
Medical Subject Headings
Algorithms; Brain (physiopathology); Brain Mapping (methods); Electroencephalography (methods); Epilepsy (diagnosis, physiopathology); Epilepsy, Temporal Lobe (diagnosis, physiopathology); Humans; Models, Neurological; Models, Statistical; Monitoring, Ambulatory (methods); Nonlinear Dynamics; Reproducibility of Results; Sensitivity and Specificity
Biomedical sciences instrumentation
Sabesan, Shivkumar; Narayanan, K; Prasad, Awadhesh; Spanias, A; Sackellares, J C.; and Iasemidis, L D., "Predictability of epileptic seizures: a comparative study using Lyapunov exponent and entropy based measures" (2003). Translational Neuroscience. 1166.