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Quantitative analysis of surface electromyography: Biomarkers for convulsive seizures

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Quantitative analysis of surface electromyography : Biomarkers for convulsive seizures. / Beniczky, Sándor; Conradsen, Isa; Pressler, Ronit; Wolf, Peter.

In: Clinical Neurophysiology, Vol. 127, No. 8, 08.2016, p. 2900-7.

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review

Harvard

Beniczky, S, Conradsen, I, Pressler, R & Wolf, P 2016, 'Quantitative analysis of surface electromyography: Biomarkers for convulsive seizures', Clinical Neurophysiology, vol. 127, no. 8, pp. 2900-7. https://doi.org/10.1016/j.clinph.2016.04.017

APA

Beniczky, S., Conradsen, I., Pressler, R., & Wolf, P. (2016). Quantitative analysis of surface electromyography: Biomarkers for convulsive seizures. Clinical Neurophysiology, 127(8), 2900-7. https://doi.org/10.1016/j.clinph.2016.04.017

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MLA

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Author

Beniczky, Sándor ; Conradsen, Isa ; Pressler, Ronit ; Wolf, Peter. / Quantitative analysis of surface electromyography : Biomarkers for convulsive seizures. In: Clinical Neurophysiology. 2016 ; Vol. 127, No. 8. pp. 2900-7.

Bibtex

@article{ca737fd180ce4c6682e42a1ef7c5de18,
title = "Quantitative analysis of surface electromyography: Biomarkers for convulsive seizures",
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.",
keywords = "Journal Article, Review",
author = "S{\'a}ndor Beniczky and Isa Conradsen and Ronit Pressler and Peter Wolf",
note = "Copyright {\textcopyright} 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.",
year = "2016",
month = aug,
doi = "10.1016/j.clinph.2016.04.017",
language = "English",
volume = "127",
pages = "2900--7",
journal = "Clinical Neurophysiology",
issn = "1388-2457",
publisher = "Elsevier Ireland Ltd.",
number = "8",

}

RIS

TY - JOUR

T1 - Quantitative analysis of surface electromyography

T2 - Biomarkers for convulsive seizures

AU - Beniczky, Sándor

AU - Conradsen, Isa

AU - Pressler, Ronit

AU - Wolf, Peter

N1 - Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

PY - 2016/8

Y1 - 2016/8

N2 - 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.

AB - 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.

KW - Journal Article

KW - Review

U2 - 10.1016/j.clinph.2016.04.017

DO - 10.1016/j.clinph.2016.04.017

M3 - Journal article

C2 - 27212115

VL - 127

SP - 2900

EP - 2907

JO - Clinical Neurophysiology

JF - Clinical Neurophysiology

SN - 1388-2457

IS - 8

ER -