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Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance
Balance during stance is regulated by active control mechanisms that continuously estimate body motion, via a “sensory integration” mechanism, and generate corrective actions, via a “sensory-to-motor transformation” mechanism. The balance control system can be modeled as a closed-loop feedback contr...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6300494/ https://www.ncbi.nlm.nih.gov/pubmed/30619027 http://dx.doi.org/10.3389/fneur.2018.01045 |
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author | Peterka, Robert J. Murchison, Charles F. Parrington, Lucy Fino, Peter C. King, Laurie A. |
author_facet | Peterka, Robert J. Murchison, Charles F. Parrington, Lucy Fino, Peter C. King, Laurie A. |
author_sort | Peterka, Robert J. |
collection | PubMed |
description | Balance during stance is regulated by active control mechanisms that continuously estimate body motion, via a “sensory integration” mechanism, and generate corrective actions, via a “sensory-to-motor transformation” mechanism. The balance control system can be modeled as a closed-loop feedback control system for which appropriate system identification methods are available to separately quantify the sensory integration and sensory-to-motor components of the system. A detailed, functionally meaningful characterization of balance control mechanisms has potential to improve clinical assessment and to provide useful tools for answering clinical research questions. However, many researchers and clinicians do not have the background to develop systems and methods appropriate for performing identification of balance control mechanisms. The purpose of this report is to provide detailed information on how to perform what we refer to as “central sensorimotor integration” (CSMI) tests on a commercially available balance test device (SMART EquiTest CRS, Natus Medical Inc, Seattle WA) and then to appropriately analyze and interpret results obtained from these tests. We describe methods to (1) generate pseudorandom stimuli that apply cyclically-repeated rotations of the stance surface and/or visual surround (2) measure and calibrate center-of-mass (CoM) body sway, (3) calculate frequency response functions (FRFs) that quantify the dynamic characteristics of stimulus-evoked CoM sway, (4) estimate balance control parameters that quantify sensory integration by measuring the relative contribution of different sensory systems to balance control (i.e., sensory weights), and (5) estimate balance control parameters that quantify sensory-to-motor transformation properties (i.e., feedback time delay and neural controller stiffness and damping parameters). Additionally, we present CSMI test results from 40 subjects (age range 21–59 years) with normal sensory function, 2 subjects with results illustrating deviations from normal balance function, and we summarize results from previous studies in subjects with vestibular deficits. A bootstrap analysis was used to characterize confidence limits on parameters from CSMI tests and to determine how test duration affected the confidence with which parameters can be measured. Finally, example results are presented that illustrate how various sensory and central balance deficits are revealed by CSMI testing. |
format | Online Article Text |
id | pubmed-6300494 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63004942019-01-07 Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance Peterka, Robert J. Murchison, Charles F. Parrington, Lucy Fino, Peter C. King, Laurie A. Front Neurol Neurology Balance during stance is regulated by active control mechanisms that continuously estimate body motion, via a “sensory integration” mechanism, and generate corrective actions, via a “sensory-to-motor transformation” mechanism. The balance control system can be modeled as a closed-loop feedback control system for which appropriate system identification methods are available to separately quantify the sensory integration and sensory-to-motor components of the system. A detailed, functionally meaningful characterization of balance control mechanisms has potential to improve clinical assessment and to provide useful tools for answering clinical research questions. However, many researchers and clinicians do not have the background to develop systems and methods appropriate for performing identification of balance control mechanisms. The purpose of this report is to provide detailed information on how to perform what we refer to as “central sensorimotor integration” (CSMI) tests on a commercially available balance test device (SMART EquiTest CRS, Natus Medical Inc, Seattle WA) and then to appropriately analyze and interpret results obtained from these tests. We describe methods to (1) generate pseudorandom stimuli that apply cyclically-repeated rotations of the stance surface and/or visual surround (2) measure and calibrate center-of-mass (CoM) body sway, (3) calculate frequency response functions (FRFs) that quantify the dynamic characteristics of stimulus-evoked CoM sway, (4) estimate balance control parameters that quantify sensory integration by measuring the relative contribution of different sensory systems to balance control (i.e., sensory weights), and (5) estimate balance control parameters that quantify sensory-to-motor transformation properties (i.e., feedback time delay and neural controller stiffness and damping parameters). Additionally, we present CSMI test results from 40 subjects (age range 21–59 years) with normal sensory function, 2 subjects with results illustrating deviations from normal balance function, and we summarize results from previous studies in subjects with vestibular deficits. A bootstrap analysis was used to characterize confidence limits on parameters from CSMI tests and to determine how test duration affected the confidence with which parameters can be measured. Finally, example results are presented that illustrate how various sensory and central balance deficits are revealed by CSMI testing. Frontiers Media S.A. 2018-12-13 /pmc/articles/PMC6300494/ /pubmed/30619027 http://dx.doi.org/10.3389/fneur.2018.01045 Text en Copyright © 2018 Peterka, Murchison, Parrington, Fino and King. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Peterka, Robert J. Murchison, Charles F. Parrington, Lucy Fino, Peter C. King, Laurie A. Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance |
title | Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance |
title_full | Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance |
title_fullStr | Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance |
title_full_unstemmed | Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance |
title_short | Implementation of a Central Sensorimotor Integration Test for Characterization of Human Balance Control During Stance |
title_sort | implementation of a central sensorimotor integration test for characterization of human balance control during stance |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6300494/ https://www.ncbi.nlm.nih.gov/pubmed/30619027 http://dx.doi.org/10.3389/fneur.2018.01045 |
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