Epileptic Seizures and the EEG: Measurement, Models, Detection and PredictionCRC Press, 2016 M04 19 - 370 pages A study of epilepsy from an engineering perspective, this volume begins by summarizing the physiology and the fundamental ideas behind the measurement, analysis and modeling of the epileptic brain. It introduces the EEG and provides an explanation of the type of brain activity likely to register in EEG measurements, offering an overview of how these EEG records are and have been analyzed in the past. The book focuses on the problem of seizure detection and surveys the physiologically based dynamic models of brain activity. Finally, it addresses the fundamental question: can seizures be predicted? Based on the authors' extensive research, the book concludes by exploring a range of future possibilities in seizure prediction. |
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action potential activity algorithms alpha rhythm amplitude analysis applied artifact auto-correlation average behavior brain channels Chapter classifier clinical CNet complex computed correlation dimension cortex cortical column cross correlation Dataset defined dendritic described detector dipoles distribution domain dynamics EEG data EEG measurement EEG records EEG signal effects electrical electrodes entropy epilepsy epileptic events epileptic seizures Equation estimate example excitatory exist expert system feature extraction filtering frequency function input inter-event intra-cranial linear Lyapunov exponents macro-scopic mathematical membrane potential meso-scopic model methods neural noise non-linear non-seizure non-stationary normal observed occur onset output parameters performance random relative resolution samples scales scalp EEG seconds Section seizure detection shown in Figure signal processing signal y[n simulated single neuron sources spatial stationarity statistics stochastic sub-systems synapses synchronization temporal thalamus typical values variables variance vector voltage volume conductor voxel waveforms wavelet window