Forecasting seizure likelihood with wearable technology
Rachel E. Stirling(The University of Melbourne), Philippa J. Karoly(The University of Melbourne), Mark P. Richardson(King's College London), Mark Cook(St Vincent's Hospital Melbourne), Ewan S. Nurse(The University of Melbourne), Daniel E. Payne(The University of Melbourne), Dean R. Freestone(The University of Melbourne), Benjamin H. Brinkmann(Mayo Clinic), Wendyl D’Souza(The University of Melbourne), David B. Grayden(The University of Melbourne), Tal Pal Attia(Mayo Clinic in Florida), Pedro F. Viana(University of Lisbon)
Cited by 8
Related Papers
Critical slowing down as a biomarker for seizure susceptibility
|Nature Communications|2020|248
Seizure forecasting and cyclic control of seizures
|Epilepsia|2020|117
Forecasting Seizure Likelihood With Wearable Technology
|Frontiers in Neurology|2021|97
Multiday cycles of heart rate are associated with seizure likelihood: An observational cohort study
|EBioMedicine|2021|89
Seizure Forecasting Using a Novel Sub-Scalp Ultra-Long Term EEG Monitoring System
|Frontiers in Neurology|2021|84