Literature DB >> 27212115

Quantitative analysis of surface electromyography: Biomarkers for convulsive seizures.

Sándor Beniczky1, Isa Conradsen2, Ronit Pressler3, Peter Wolf4.   

Abstract

Muscle activity during seizures is in electroencephalographical (EEG) praxis often considered an irritating artefact. This article discusses ways by surface electromyography (EMG) to turn it into a valuable tool of epileptology. Muscles are in direct synaptic contact with motor neurons. Therefore, EMG signals provide direct information about the electric activity in the motor cortex. Qualitative analysis of EMG has traditionally been a part of the long-term video-EEG recordings. Recent development in quantitative analysis of EMG signals yielded valuable information on the pathomechanisms of convulsive seizures, demonstrating that it was different from maximal voluntary contraction, and different from convulsive psychogenic non-epileptic seizures. Furthermore, the tonic phase of the generalised tonic-clonic seizures (GTCS) proved to have different quantitative features than tonic seizures. The high temporal resolution of EMG allowed detailed characterisation of temporal dynamics of the GTCS, suggesting that the same inhibitory mechanisms that try to prevent the build-up of the seizure activity, contribute to ending the seizure. These findings have clinical implications: the quantitative EMG features provided the pathophysiologic substrate for developing neurophysiologic biomarkers that accurately identify GTCS. This proved to be efficient both for seizure detection and for objective, automated distinction between convulsive and non-convulsive epileptic seizures.
Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Biomarkers; EMG; Seizure-detection; Tonic; Tonic–clonic seizures

Mesh:

Substances:

Year:  2016        PMID: 27212115     DOI: 10.1016/j.clinph.2016.04.017

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


  6 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.  Bibliometric Analysis of Quantitative Electroencephalogram Research in Neuropsychiatric Disorders From 2000 to 2021.

Authors:  Shun Yao; Jieying Zhu; Shuiyan Li; Ruibin Zhang; Jiubo Zhao; Xueling Yang; You Wang
Journal:  Front Psychiatry       Date:  2022-05-23       Impact factor: 5.435

3.  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

Review 4.  Automatic Computer-Based Detection of Epileptic Seizures.

Authors:  Christoph Baumgartner; Johannes P Koren; Michaela Rothmayer
Journal:  Front Neurol       Date:  2018-08-09       Impact factor: 4.003

5.  Subcutaneous EEG Monitoring Reveals AED Response and Breakthrough Seizures.

Authors:  Sigge Weisdorf; Ivan C Zibrandtsen; Troels W Kjaer
Journal:  Case Rep Neurol Med       Date:  2020-01-28

Review 6.  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

  6 in total

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