Literature DB >> 27454332

Automated non-EEG based seizure detection: Do users have a say?

Anouk Van de Vel1, Katrien Smets2, Kristien Wouters3, Berten Ceulemans4.   

Abstract

PURPOSE: Quality of life of patients with epilepsy depends largely upon unpredictability of seizure occurrence and would improve by predicting seizures or at least by detecting seizures (after their clinical onset) and react timely. Detection systems are available and researched, but little is known about the actual need and user preferences. The first indicates the market potential; the second allows us to incorporate user requirements into the engineering process.
METHODS: We questioned 20 pediatric and young adult patients, 114 caregivers, and 21 involved medical doctors and described, analyzed, and compared their experiences with systems for seizure detection, their opinions on usefulness and purpose of seizure detection, and their requirements for such a device.
RESULTS: Experience with detection systems is limited, but 65% of patients and caregivers and 85% of medical doctors express the usefulness, more so during night than day. The need is higher in patients with more severe intellectual disability. The higher the seizure frequency, the higher the need, opinions in the seizure-free group being more divided. Most patients and caregivers require 100% correct detection, and on average, one false alarm per seizure (one per week for those seizure-free) is accepted. Medical doctors allow 90% correct detections and between two false alarms per week and one per month depending on seizure frequency. Detection of seizures involving heavy movement and falls is judged most important by patients and caregivers and second to most by medical doctors. The latter judge heart rate monitoring most relevant, both towards seizure detection and SUDEP (sudden unexpected death in epilepsy) prevention.
CONCLUSIONS: The results, including a goal of 90% correct detections and one false alarm per seizure, should be considered in development of seizure detectors.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Alarm system; Epilepsy; Experience; Questionnaire; Requirements; Usefulness

Mesh:

Year:  2016        PMID: 27454332     DOI: 10.1016/j.yebeh.2016.06.029

Source DB:  PubMed          Journal:  Epilepsy Behav        ISSN: 1525-5050            Impact factor:   2.937


  9 in total

Review 1.  Seizure detection: do current devices work? And when can they be useful?

Authors:  Xiuhe Zhao; Samden D Lhatoo
Journal:  Curr Neurol Neurosci Rep       Date:  2018-05-23       Impact factor: 5.081

2.  Automated real-time detection of tonic-clonic seizures using a wearable EMG device.

Authors:  Sándor Beniczky; Isa Conradsen; Oliver Henning; Martin Fabricius; Peter Wolf
Journal:  Neurology       Date:  2018-01-05       Impact factor: 9.910

3.  A Patient Perspective on Seizure Detection and Forecasting.

Authors:  Aria Moss; Evan Moss; Robert Moss; Lisa Moss; Sharon Chiang; Peter Crino
Journal:  Front Neurol       Date:  2022-02-11       Impact factor: 4.003

4.  Parental preferences for seizure detection devices: A discrete choice experiment.

Authors:  Anouk van Westrhenen; Ben F M Wijnen; Roland D Thijs
Journal:  Epilepsia       Date:  2022-03-04       Impact factor: 6.740

5.  Multimodal nocturnal seizure detection: Do we need to adapt algorithms for children?

Authors:  Richard H C Lazeron; Roland D Thijs; Johan Arends; Thea Gutter; Pierre Cluitmans; Johannes Van Dijk; Francis I Y Tan; Wytske Hofstra; Claire E H M Donjacour; Frans Leijten
Journal:  Epilepsia Open       Date:  2022-07-21

6.  Automated seizure detection with noninvasive wearable devices: A systematic review and meta-analysis.

Authors:  Vaidehi Naganur; Shobi Sivathamboo; Zhibin Chen; Shitanshu Kusmakar; Ana Antonic-Baker; Terence J O'Brien; Patrick Kwan
Journal:  Epilepsia       Date:  2022-05-28       Impact factor: 6.740

7.  Detection of generalized tonic-clonic seizures using surface electromyographic monitoring.

Authors:  Jonathan J Halford; Michael R Sperling; Dileep R Nair; Dennis J Dlugos; William O Tatum; Jay Harvey; Jacqueline A French; John R Pollard; Edward Faught; Katherine H Noe; Thomas R Henry; Gina M Jetter; Octavian V Lie; Lola C Morgan; Michael R Girouard; Damon P Cardenas; Luke E Whitmire; Jose E Cavazos
Journal:  Epilepsia       Date:  2017-10-05       Impact factor: 5.864

8.  Multimodal nocturnal seizure detection in a residential care setting: A long-term prospective trial.

Authors:  Johan Arends; Roland D Thijs; Thea Gutter; Constantin Ungureanu; Pierre Cluitmans; Johannes Van Dijk; Judith van Andel; Francis Tan; Al de Weerd; Ben Vledder; Wytske Hofstra; Richard Lazeron; Ghislaine van Thiel; Kit C B Roes; Frans Leijten
Journal:  Neurology       Date:  2018-10-24       Impact factor: 9.910

9.  Evaluation of a collar-mounted accelerometer for detecting seizure activity in dogs.

Authors:  Karen R Muñana; Julie A Nettifee; Emily H Griffith; Peter J Early; Nathanael C Yoder
Journal:  J Vet Intern Med       Date:  2020-04-15       Impact factor: 3.333

  9 in total

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