title: Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy.
abstract: Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy.
authors.affiliation: Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA; Department of Pediatrics, Children's Hospital of Pittsburgh, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
authors.forename: Sriram
authors.initials: S
authors.lastname: Ramgopal
authors.affiliation: Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA; Psychiatry Department of Clinics Hospital of School of Medicine of University of Sao Paulo, Brazil.
authors.forename: Sigride
authors.initials: S
authors.lastname: Thome-Souza
authors.affiliation: Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA.
authors.forename: Michele
authors.initials: M
authors.lastname: Jackson
authors.affiliation: Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA; Department of Neuropediatrics and Department of Medical Psychology and Medical Sociology, University Medical Center Schleswig-Holstein, Christian-Albrechts-University, Kiel, Germany.
authors.forename: Navah Ester
authors.initials: NE
authors.lastname: Kadish
authors.affiliation: Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA.
authors.forename: Iván
authors.initials: I
authors.lastname: Sánchez Fernández
authors.affiliation: Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA.
authors.forename: Jacquelyn
authors.initials: J
authors.lastname: Klehm
authors.affiliation: Department of Health Informatics, University of San Francisco School of Nursing and Health Professions, San Francisco, CA, USA.
authors.forename: William
authors.initials: W
authors.lastname: Bosl
authors.affiliation: Edward B. Bromfield Epilepsy Center, Dept. of Neurology, Brigham and Women's Hospital, Boston, MA, USA; Institute of Sports Medicine, Department of Exercise and Health, Faculty of Science, University of Paderborn, Germany; Institute of Sports Medicine, Faculty of Science, University of Paderborn, Warburger Str. 100, 33098 Paderborn, Germany.
authors.forename: Claus
authors.initials: C
authors.lastname: Reinsberger
authors.affiliation: Department of Neurology, Harvard Medical School, Boston, MA, USA.
authors.forename: Steven
authors.initials: S
authors.lastname: Schachter
authors.affiliation: Division of Epilepsy and Clinical Neurophysiology, Department of Neurology, Boston Children's Hospital, Boston, MA, USA. Electronic address: tobias.loddenkemper@childrens.harvard.edu.
authors.forename: Tobias
authors.initials: T
authors.lastname: Loddenkemper
mesh_terms: D000293:Adolescent; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D004562:Electrocardiography / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis*; D006801:Humans; D008390:Markov Chains; D009038:Motion; D011237:Predictive Value of Tests; D012535:Scalp; D012640:Seizures / Q000175:diagnosis*; D012680:Sensitivity and Specificity
keywords: Accelerometry; Artificial neural network; Automated seizure detection; Closed-loop methods; ECG-based seizure detection; EEG-based seizure detection; Fourier; Higher-order spectra; Markov modeling; Support vector machine