TY - CHAP M1 - Book, Section TI - Automated Analysis of EEG A1 - Gardner, Andrew A1 - Stead, S. Matt A1 - Worrell, Greg A. A2 - Sirven, Joseph I. A2 - Stern, John M. Y1 - 2011 N1 - T2 - Atlas of Video-EEG Monitoring AB - The electroencephalogram (EEG) provides a real-time measure of brain electrical activity and has proven to be useful in a wide range of clinical settings, for example, evaluation of seizures, mental status change, coma, and classification of epilepsy.1,2 The clinical applications of continuous EEG monitoring can involve recordings from scalp or intracranial electrodes obtained in the hospital (e.g., video scalp and intracranial EEG [IEEG] monitoring), on an outpatient basis (routine scalp EEG), and even in nonmedical settings (ambulatory EEG). More recently, a cranially implanted device (the RNS system, NeuroPace Inc.) using continuous IEEG for real-time seizure detection and electrical stimulation to abort seizures is undergoing clinical trial.3 This broad range of clinical applications underscores the usefulness of EEG for studying brain dysfunction and highlights the potential applications of automated EEG analysis. In this chapter, we give an overview of automated detection of epileptiform activity. The primary goal is to discuss epileptiform event detection in the context of modern data mining and pattern recognition.4–6 The chapter is not intended to be a comprehensive review of epileptiform spike and seizure detection.7–10 SN - PB - McGraw-Hill Education CY - New York, NY Y2 - 2024/03/28 UR - neurology.mhmedical.com/content.aspx?aid=1103048537 ER -