Literature DB >> 33678577

Automated seizure detection using wearable devices: A clinical practice guideline of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology.

Sándor Beniczky1, Samuel Wiebe2, Jesper Jeppesen3, William O Tatum4, Milan Brazdil5, Yuping Wang6, Susan T Herman7, Philippe Ryvlin8.   

Abstract

The objective of this clinical practice guideline (CPG) is to provide recommendations for healthcare personnel working with patients with epilepsy, on the use of wearable devices for automated seizure detection in patients with epilepsy, in outpatient, ambulatory settings. The Working Group of the International League Against Epilepsy and the International Federation of Clinical Neurophysiology developed the CPG according to the methodology proposed by the ILAE Epilepsy Guidelines Working Group. We reviewed the published evidence using The Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement and evaluated the evidence and formulated the recommendations following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. We found high level of evidence for the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) and focal-to-bilateral tonic-clonic seizures (FBTCS) and recommend use of wearable automated seizure detection devices for selected patients when accurate detection of GTCS and FBTCS is recommended as a clinical adjunct. We also found moderate level of evidence for seizure types without GTCs or FBTCs. However, it was uncertain whether the detected alarms resulted in meaningful clinical outcomes for the patients. We recommend using clinically validated devices for automated detection of GTCS and FBTCS, especially in unsupervised patients, where alarms can result in rapid intervention (weak/conditional recommendation). At present, we do not recommend clinical use of the currently available devices for other seizure types (weak/conditional recommendation). Further research and development are needed to improve the performance of automated seizure detection and to document their accuracy and clinical utility.
Copyright © 2021 International Federation of Clinical Neurophysiology, Inc., International League Against Epilepsia. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Algorithms; Automated detection; Epilepsy; Seizure detection; Wearable devices

Year:  2021        PMID: 33678577     DOI: 10.1016/j.clinph.2020.12.009

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  8 in total

1.  Extreme value theory inspires explainable machine learning approach for seizure detection.

Authors:  Oleg E Karpov; Vadim V Grubov; Vladimir A Maksimenko; Semen A Kurkin; Nikita M Smirnov; Nikita P Utyashev; Denis A Andrikov; Natalia N Shusharina; Alexander E Hramov
Journal:  Sci Rep       Date:  2022-07-06       Impact factor: 4.996

Review 2.  The Prospects of Non-EEG Seizure Detection Devices in Dogs.

Authors:  Jos Bongers; Rodrigo Gutierrez-Quintana; Catherine Elizabeth Stalin
Journal:  Front Vet Sci       Date:  2022-05-23

3.  Ambulatory seizure forecasting with a wrist-worn device using long-short term memory deep learning.

Authors:  Mona Nasseri; Tal Pal Attia; Boney Joseph; Nicholas M Gregg; Ewan S Nurse; Pedro F Viana; Gregory Worrell; Matthias Dümpelmann; Mark P Richardson; Dean R Freestone; Benjamin H Brinkmann
Journal:  Sci Rep       Date:  2021-11-09       Impact factor: 4.379

Review 4.  Current advances and challenges in nanosheet-based wearable power supply devices.

Authors:  Sheng Zhang; Qingchao Xia; Shuyang Ma; Wei Yang; Qianqian Wang; Canjun Yang; Bo Jin; Chen Liu
Journal:  iScience       Date:  2021-11-19

5.  Proposal for an updated seizure classification framework in clinical trials.

Authors:  Claude Steriade; Michael R Sperling; Bree DiVentura; Meryl Lozano; Renée A Shellhaas; Sudha Kilaru Kessler; Dennis Dlugos; Jacqueline French
Journal:  Epilepsia       Date:  2022-01-07       Impact factor: 6.740

6.  Automated detection of nocturnal motor seizures using an audio-video system.

Authors:  Sidsel Armand Larsen; Daniella Terney; Tim Østerkjerhuus; Torsten Vinding Merinder; Kaapo Annala; Andrew Knight; Sándor Beniczky
Journal:  Brain Behav       Date:  2022-08-08       Impact factor: 3.405

Review 7.  Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic.

Authors:  Benjamin H Brinkmann; Philippa J Karoly; Ewan S Nurse; Sonya B Dumanis; Mona Nasseri; Pedro F Viana; Andreas Schulze-Bonhage; Dean R Freestone; Greg Worrell; Mark P Richardson; Mark J Cook
Journal:  Front Neurol       Date:  2021-07-13       Impact factor: 4.003

Review 8.  Noninvasive mobile EEG as a tool for seizure monitoring and management: A systematic review.

Authors:  Andrea Biondi; Viviana Santoro; Pedro F Viana; Petroula Laiou; Deb K Pal; Elisa Bruno; Mark P Richardson
Journal:  Epilepsia       Date:  2022-03-27       Impact factor: 6.740

  8 in total

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