title: Tracking generalized tonic-clonic seizures with a wrist accelerometer linked to an online database.
abstract: OBJECTIVE
  Clinical management of epilepsy and current epilepsy therapy trials rely on paper or electronic diaries often with inaccurate self-reported seizure frequency as the primary outcome. This is the first study addressing the feasibility of detecting and recording generalized tonic-clonic seizures (GTCS) through a biosensor linked to an online seizure database.
  
  
  METHODS
  A prospective trial was conducted with video-EEG (vEEG) in an epilepsy monitoring unit. Patients wore a wristwatch accelerometer that detected shaking and transmitted events via Bluetooth® to a bedside electronic tablet and then via Wi-Fi to an online portal. The watch recorded the date, time, audio, duration, frequency and amplitude of events. Events logged by the watch and recorded in a bedside paper diary were measured against vEEG, the "gold standard."
  
  
  RESULTS
  Thirty patients were enrolled and 62 seizures were recorded on vEEG: 31 convulsive and 31 non-convulsive. Twelve patients had a total of 31 convulsive seizures, and of those, 10 patients had 13 GTCS. The watch captured 12/13 (92.3%) GTCS. Watch audio recordings were consistent with seizures in 11/12 (91.6%). Data were successfully transferred to the bedside tablet in 11/12 (91.6%), and to the online database in 10/12 (83.3%) GTCS. The watch recorded 81 false positives, of which 42/81 (51%) were cancelled by the patients. Patients and caregivers verbally reported 15/62 seizures (24.2% sensitivity) but no seizures were recorded on paper logs.
  
  
  CONCLUSIONS
  Automatic detection and recording of GTCS to an online database is feasible and may be more informative than seizure logging in a paper diary.
authors.affiliation: Stanford University School of Medicine, Department of Neurology, Stanford Comprehensive Epilepsy Center, 213 Quarry Drive, 5979, Palo Alto, CA, 94304, USA.
authors.forename: Mariel
authors.initials: M
authors.lastname: Velez
authors.affiliation: Stanford University School of Medicine, Department of Neurology, Stanford Comprehensive Epilepsy Center, 213 Quarry Drive, 5979, Palo Alto, CA, 94304, USA.
authors.forename: Robert S
authors.initials: RS
authors.lastname: Fisher
authors.affiliation: Harvard University, Cambridge, MA, USA.
authors.forename: Victoria
authors.initials: V
authors.lastname: Bartlett
authors.affiliation: Stanford University School of Medicine, Department of Neurology, Stanford Comprehensive Epilepsy Center, 213 Quarry Drive, 5979, Palo Alto, CA, 94304, USA. Electronic address: schele@stanford.edu.
authors.forename: Scheherazade
authors.initials: S
authors.lastname: Le
mesh_terms: D061725:Accelerometry / Q000295:instrumentation / Q000379:methods*; D000328:Adult; D000368:Aged; D016208:Databases, Factual; D004569:Electroencephalography / Q000379:methods*; D004830:Epilepsy, Tonic-Clonic / Q000175:diagnosis*; D005260:Female; D006801:Humans; D020407:Internet; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000295:instrumentation / Q000379:methods*; D011446:Prospective Studies; D014741:Video Recording; D055815:Young Adult
keywords: Automatic detection; Epilepsy; Online interface; Seizure diary