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Tensometric tremorography in high-precision medical diagnostic systems

BACKGROUND: The objective of the study was to develop a system for the precision diagnostics of pathologies of motor brain regions based on tensometric measurement and to explore its diagnostic capabilities. MATERIALS AND METHODS: Tremor is a syndrome that indicates the abnormal state of the central...

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Autores principales: Aleksanyan, Zoya, Bureneva, Olga, Safyannikov, Nikolay
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6145354/
https://www.ncbi.nlm.nih.gov/pubmed/30271224
http://dx.doi.org/10.2147/MDER.S168831
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author Aleksanyan, Zoya
Bureneva, Olga
Safyannikov, Nikolay
author_facet Aleksanyan, Zoya
Bureneva, Olga
Safyannikov, Nikolay
author_sort Aleksanyan, Zoya
collection PubMed
description BACKGROUND: The objective of the study was to develop a system for the precision diagnostics of pathologies of motor brain regions based on tensometric measurement and to explore its diagnostic capabilities. MATERIALS AND METHODS: Tremor is a syndrome that indicates the abnormal state of the central nervous system, primarily in the motor brain regions. Analysis of tremor parameters provides significant information about the changes in the body motion control and can be used as an objective index of the central nervous system state. Existing methods are aimed at the analysis of visible tremor based on the use of different sensors. We suggest an alternative approach based on the use of a tensometric system performing tremor measurements when the tremor appears on the background of voluntary isometric efforts. The key advantage of our approach is that it allows to determine the tremor before its visible manifestation. In the article, we describe hardware implementation of our tremor analysis system. RESULTS: In the article, we represent the new methodology and the original equipment based on the control of isometric effort. Isometric effort formed by a patient is controlled with the use of a feedback system on the patient’s monitor. We evaluated the performance of our equipment with more than 400 healthy volunteers and patients with various pathologies of the central nervous system motor regions, and the results of the investigations, allowing to identify tremor parameters typical for parkinsonism, are represented in our article. CONCLUSION: Testing of the system confirmed its high diagnostic validity and reliability, high sensitivity, simplicity and high speed of information processing. The approach based on tensometric measurements is very promising for the diagnostics of Parkinson disease and dysfunctions of a central nervous system.
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spelling pubmed-61453542018-09-28 Tensometric tremorography in high-precision medical diagnostic systems Aleksanyan, Zoya Bureneva, Olga Safyannikov, Nikolay Med Devices (Auckl) Original Research BACKGROUND: The objective of the study was to develop a system for the precision diagnostics of pathologies of motor brain regions based on tensometric measurement and to explore its diagnostic capabilities. MATERIALS AND METHODS: Tremor is a syndrome that indicates the abnormal state of the central nervous system, primarily in the motor brain regions. Analysis of tremor parameters provides significant information about the changes in the body motion control and can be used as an objective index of the central nervous system state. Existing methods are aimed at the analysis of visible tremor based on the use of different sensors. We suggest an alternative approach based on the use of a tensometric system performing tremor measurements when the tremor appears on the background of voluntary isometric efforts. The key advantage of our approach is that it allows to determine the tremor before its visible manifestation. In the article, we describe hardware implementation of our tremor analysis system. RESULTS: In the article, we represent the new methodology and the original equipment based on the control of isometric effort. Isometric effort formed by a patient is controlled with the use of a feedback system on the patient’s monitor. We evaluated the performance of our equipment with more than 400 healthy volunteers and patients with various pathologies of the central nervous system motor regions, and the results of the investigations, allowing to identify tremor parameters typical for parkinsonism, are represented in our article. CONCLUSION: Testing of the system confirmed its high diagnostic validity and reliability, high sensitivity, simplicity and high speed of information processing. The approach based on tensometric measurements is very promising for the diagnostics of Parkinson disease and dysfunctions of a central nervous system. Dove Medical Press 2018-09-13 /pmc/articles/PMC6145354/ /pubmed/30271224 http://dx.doi.org/10.2147/MDER.S168831 Text en © 2018 Aleksanyan et al. This work is published and licensed by Dove Medical Press Limited The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Aleksanyan, Zoya
Bureneva, Olga
Safyannikov, Nikolay
Tensometric tremorography in high-precision medical diagnostic systems
title Tensometric tremorography in high-precision medical diagnostic systems
title_full Tensometric tremorography in high-precision medical diagnostic systems
title_fullStr Tensometric tremorography in high-precision medical diagnostic systems
title_full_unstemmed Tensometric tremorography in high-precision medical diagnostic systems
title_short Tensometric tremorography in high-precision medical diagnostic systems
title_sort tensometric tremorography in high-precision medical diagnostic systems
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6145354/
https://www.ncbi.nlm.nih.gov/pubmed/30271224
http://dx.doi.org/10.2147/MDER.S168831
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