Literature DB >> 29873829

Detection of convulsive seizures using surface electromyography.

Sándor Beniczky1,2, Isa Conradsen3, Peter Wolf1,4.   

Abstract

Bilateral (generalized) tonic-clonic seizures (TCS) increase the risk of sudden unexpected death in epilepsy (SUDEP), especially when patients are unattended. In sleep, TCS often remain unnoticed, which can result in suboptimal treatment decisions. There is a need for automated detection of these major epileptic seizures, using wearable devices. Quantitative surface electromyography (EMG) changes are specific for TCS and characterized by a dynamic evolution of low- and high-frequency signal components. Algorithms targeting increase in high-frequency EMG signals constitute biomarkers of TCS; they can be used both for seizure detection and for differentiating TCS from convulsive nonepileptic seizures. Two large-scale, blinded, prospective studies demonstrated the accuracy of wearable EMG devices for detecting TCS with high sensitivity (76%-100%). The rate of false alarms (0.7-2.5/24 h) needs further improvement. This article summarizes the pathophysiology of muscle activation during convulsive seizures and reviews the published evidence on the accuracy of EMG-based seizure detection. Wiley Periodicals, Inc.
© 2018 International League Against Epilepsy.

Entities:  

Keywords:  Seizure detection; biomarkers; electromyography; tonic; tonic-clonic seizures

Mesh:

Year:  2018        PMID: 29873829     DOI: 10.1111/epi.14048

Source DB:  PubMed          Journal:  Epilepsia        ISSN: 0013-9580            Impact factor:   5.864


  7 in total

1.  Seizure Detection Devices: Five New Things.

Authors:  Alexandra Carrick Atwood; Cornelia Natasha Drees
Journal:  Neurol Clin Pract       Date:  2021-10

2.  Ultra-long-term subcutaneous home monitoring of epilepsy-490 days of EEG from nine patients.

Authors:  Sigge Weisdorf; Jonas Duun-Henriksen; Marianne J Kjeldsen; Frantz R Poulsen; Sirin W Gangstad; Troels W Kjaer
Journal:  Epilepsia       Date:  2019-10-13       Impact factor: 5.864

3.  Wearable Epileptic Seizure Prediction System with Machine-Learning-Based Anomaly Detection of Heart Rate Variability.

Authors:  Toshitaka Yamakawa; Miho Miyajima; Koichi Fujiwara; Manabu Kano; Yoko Suzuki; Yutaka Watanabe; Satsuki Watanabe; Tohru Hoshida; Motoki Inaji; Taketoshi Maehara
Journal:  Sensors (Basel)       Date:  2020-07-17       Impact factor: 3.576

Review 4.  Future opportunities for research in rescue treatments.

Authors:  James W Wheless; Daniel Friedman; Gregory L Krauss; Vikram R Rao; Michael R Sperling; Enrique Carrazana; Adrian L Rabinowicz
Journal:  Epilepsia       Date:  2022-09       Impact factor: 6.740

5.  Electrographic seizure monitoring with a novel, wireless, single-channel EEG sensor.

Authors:  Mitchell A Frankel; Mark J Lehmkuhle; Meagan Watson; Kirsten Fetrow; Lauren Frey; Cornelia Drees; Mark C Spitz
Journal:  Clin Neurophysiol Pract       Date:  2021-05-29

Review 6.  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 7.  Noninvasive detection of focal seizures in ambulatory patients.

Authors:  Philippe Ryvlin; Leila Cammoun; Ilona Hubbard; France Ravey; Sandor Beniczky; David Atienza
Journal:  Epilepsia       Date:  2020-06-02       Impact factor: 5.864

  7 in total

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