Cited by 233Epilepsy research and treatmentEEG and Brain-Computer InterfacesSeismology and Earthquake Studies

Automated seizure detection systems and their effectiveness for each type of seizure

Open access
Ulate-Campos, A., Coughlin, F., Gaínza-Lein, M., Fernández, I. Sánchez, Pearl, P.L., Loddenkemper, T.·2016·Seizure

Abstract

Epilepsy affects almost 1% of the population and most of the approximately 20-30% of patients with refractory epilepsy have one or more seizures per month. Seizure detection devices allow an objective assessment of seizure frequency and a treatment tailored to the individual patient. A rapid recognition and treatment of seizures through closed-loop systems could potentially decrease morbidity and mortality in epilepsy. However, no single detection device can detect all seizure types. Therefore, the choice of a seizure detection device should consider the patient-specific seizure semiologies. This review of the literature evaluates seizure detection devices and their effectiveness for different seizure types. Our aim is to summarize current evidence, offer suggestions on how to select the most suitable seizure detection device for each patient and provide guidance to physicians, families and researchers when choosing or designing seizure detection devices. Further, this review will guide future prospective validation studies.

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Crossref · 10.1016/j.seizure.2016.06.008

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  • Seizure monitoring, compared to many other clinical applications, requires a high temporal resolution, as seizures can be as short as a few seconds.

    “Seizure monitoring, compared to many other clinical applications, requires a high temporal resolution, as seizures can be as short as a few seconds17–19”

    From Data quality evaluation in wearable monitoring (2022) · cites this paper as [19]

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  1. Hoppe C, Poepel A, Elger CE. Epilepsy: accuracy of patient seizure counts. Arch Neurol 2007;64(11):1595-9.

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Authors
Ulate-Campos, A., Coughlin, F., Gaínza-Lein, M., Fernández, I. S., Pearl, P. L., & Loddenkemper, T.
Affiliations
  • Hospital Nacional de Niños (CR)
  • Boston Children's Hospital (US)
Corresponding author
  • Ulate-Campos, A.
  • Coughlin, F.
  • Fernández, I. Sánchez
  • Pearl, P.L.
  • Loddenkemper, T.
Venue
Seizure
Publisher
Elsevier BV
Published
2016-08
Volume
40
Pages
88-101
ISSN
1059-1311 (ISSN-L)
OpenAlex
W2422080706
Cited by
233
References
140
Citations by year
2026: 6 · 2025: 20 · 2024: 20 · 2023: 29 · 2022: 23 · 2021: 37 · 2020: 29 · 2019: 26 · 2018: 32 · 2017: 8 · 2016: 3
FWCI
3.28
Type
journal article
Language
en
Open access
Locations
  • Seizure (publishedVersion)
  • PubMed (publishedVersion)
Funders
Epilepsy Research Fund
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Epilepsy research and treatment
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Physical Sciences › Computer Science › Artificial Intelligence › Seismology and Earthquake Studies
Keywords
epilepsy, drug-resistant epilepsy, seizure types, closed-loop systems, device selection, device validation, seizure semiology
MeSH terms
Humans, Seizures, Neurophysiological Monitoring

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