title: Seizure reporting technologies for epilepsy treatment: A review of clinical information needs and supporting technologies.
abstract: This review surveys current seizure detection and classification technologies as they relate to aiding clinical decision-making during epilepsy treatment. Interviews and data collected from neurologists and a literature review highlighted a strong need for better distinguishing between patients exhibiting generalized and partial seizure types as well as achieving more accurate seizure counts. This information is critical for enabling neurologists to select the correct class of antiepileptic drugs (AED) for their patients and evaluating AED efficiency during long-term treatment. In our questionnaire, 100% of neurologists reported they would like to have video from patients prior to selecting an AED during an initial consultation. Presently, only 30% have access to video. In our technology review we identified that only a subset of available technologies surpassed patient self-reporting performance due to high false positive rates. Inertial seizure detection devices coupled with video capture for recording seizures at night could stand to address collecting seizure counts that are more accurate than current patient self-reporting during day and night time use.
authors.affiliation: School of Interactive Computing, Georgia Institute of Technology, 85 Fifth Street NW Atlanta, GA, USA. Electronic address: bidwej@gatech.edu.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Bidwell
authors.affiliation: School of Interactive Computing, Georgia Institute of Technology, 85 Fifth Street NW Atlanta, GA, USA.
authors.forename: Thanin
authors.initials: T
authors.lastname: Khuwatsamrit
authors.affiliation: School of Medicine, Emory University, 1648 Pierce Dr NE, Atlanta, GA, USA.
authors.forename: Brittain
authors.initials: B
authors.lastname: Askew
authors.affiliation: School of Medicine, Emory University, 1648 Pierce Dr NE, Atlanta, GA, USA.
authors.forename: Joshua Andrew
authors.initials: JA
authors.lastname: Ehrenberg
authors.affiliation: School of Medicine, Emory University, 1648 Pierce Dr NE, Atlanta, GA, USA.
authors.forename: Sandra
authors.initials: S
authors.lastname: Helmers
mesh_terms: D000927:Anticonvulsants / Q000627:therapeutic use; D004568:Electrodiagnosis / Q000295:instrumentation* / Q000379:methods; D004827:Epilepsy / Q000145:classification / Q000175:diagnosis / Q000503:physiopathology / Q000628:therapy*; D006801:Humans; D008991:Monitoring, Physiologic / Q000295:instrumentation* / Q000379:methods; D012640:Seizures / Q000145:classification / Q000175:diagnosis / Q000503:physiopathology / Q000628:therapy*; D057566:Self Report; D014741:Video Recording / Q000295:instrumentation* / Q000379:methods
chemical_list: D000927:Anticonvulsants
keywords: Epilepsy, Seizure reporting, Accelerometry, Non-EEG seizure detection, ECG-based seizure detection, Automated seizure detection