Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation
Abstract Background Closed loop system identification (CLSIT) is a method to disentangle the contribution of underlying systems in standing balance. We investigated whether taking into account lower leg muscle activation in CLSIT could improve the reliability and accuracy of estimated parameters ide...
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doaj-2e6e2fbb82d1416b819bd5ff36ee90b32020-11-24T21:02:16ZengBMCJournal of NeuroEngineering and Rehabilitation1743-00032017-09-0114111710.1186/s12984-017-0299-xAssessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimationJ. H. Pasma0J. van Kordelaar1D. de Kam2V. Weerdesteyn3A. C. Schouten4H. van der Kooij5Department of Biomechanical Engineering, Delft University of TechnologyDepartment of Biomechanical Engineering, Institute for Biomedical Technology and Technical Medicine (MIRA), University of TwenteDepartment of Rehabilitation, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterDepartment of Rehabilitation, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical CenterDepartment of Biomechanical Engineering, Delft University of TechnologyDepartment of Biomechanical Engineering, Delft University of TechnologyAbstract Background Closed loop system identification (CLSIT) is a method to disentangle the contribution of underlying systems in standing balance. We investigated whether taking into account lower leg muscle activation in CLSIT could improve the reliability and accuracy of estimated parameters identifying the underlying systems. Methods Standing balance behaviour of 20 healthy young participants was measured using continuous rotations of the support surface (SS). The dynamic balance behaviour obtained with CLSIT was expressed by sensitivity functions of the ankle torque, body sway and muscle activation of the lower legs to the SS rotation. Balance control models, 1) without activation dynamics, 2) with activation dynamics and 3) with activation dynamics and acceleration feedback, were fitted on the data of all possible combinations of the 3 sensitivity functions. The reliability of the estimated model parameters was represented by the mean relative standard errors of the mean (mSEM) of the estimated parameters, expressed for the basic parameters, the activation dynamics parameters and the acceleration feedback parameter. To investigate the accuracy, a model validation study was performed using simulated data obtained with a comprehensive balance control model. The accuracy of the estimated model parameters was described by the mean relative difference (mDIFF) between the estimated parameters and original parameters. Results The experimental data showed a low mSEM of the basic parameters, activation dynamics parameters and acceleration feedback parameter by adding muscle activation in combination with activation dynamics and acceleration feedback to the fitted model. From the simulated data, the mDIFF of the basic parameters varied from 22.2–22.4% when estimated using the torque and body sway sensitivity functions. Adding the activation dynamics, acceleration feedback and muscle activation improved mDIFF to 13.1–15.1%. Conclusions Adding the muscle activation in combination with the activation dynamics and acceleration feedback to CLSIT improves the accuracy and reliability of the estimated parameters and gives the possibility to separate the neural time delay, electromechanical delay and the intrinsic and reflexive dynamics. To diagnose impaired balance more specifically, it is recommended to add electromyography (EMG) to body sway (with or without torque) measurements in the assessment of the underlying systems.http://link.springer.com/article/10.1186/s12984-017-0299-xPostureHuman balance controlModellingMuscle activationActivation dynamics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
J. H. Pasma J. van Kordelaar D. de Kam V. Weerdesteyn A. C. Schouten H. van der Kooij |
spellingShingle |
J. H. Pasma J. van Kordelaar D. de Kam V. Weerdesteyn A. C. Schouten H. van der Kooij Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation Journal of NeuroEngineering and Rehabilitation Posture Human balance control Modelling Muscle activation Activation dynamics |
author_facet |
J. H. Pasma J. van Kordelaar D. de Kam V. Weerdesteyn A. C. Schouten H. van der Kooij |
author_sort |
J. H. Pasma |
title |
Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation |
title_short |
Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation |
title_full |
Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation |
title_fullStr |
Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation |
title_full_unstemmed |
Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation |
title_sort |
assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation |
publisher |
BMC |
series |
Journal of NeuroEngineering and Rehabilitation |
issn |
1743-0003 |
publishDate |
2017-09-01 |
description |
Abstract Background Closed loop system identification (CLSIT) is a method to disentangle the contribution of underlying systems in standing balance. We investigated whether taking into account lower leg muscle activation in CLSIT could improve the reliability and accuracy of estimated parameters identifying the underlying systems. Methods Standing balance behaviour of 20 healthy young participants was measured using continuous rotations of the support surface (SS). The dynamic balance behaviour obtained with CLSIT was expressed by sensitivity functions of the ankle torque, body sway and muscle activation of the lower legs to the SS rotation. Balance control models, 1) without activation dynamics, 2) with activation dynamics and 3) with activation dynamics and acceleration feedback, were fitted on the data of all possible combinations of the 3 sensitivity functions. The reliability of the estimated model parameters was represented by the mean relative standard errors of the mean (mSEM) of the estimated parameters, expressed for the basic parameters, the activation dynamics parameters and the acceleration feedback parameter. To investigate the accuracy, a model validation study was performed using simulated data obtained with a comprehensive balance control model. The accuracy of the estimated model parameters was described by the mean relative difference (mDIFF) between the estimated parameters and original parameters. Results The experimental data showed a low mSEM of the basic parameters, activation dynamics parameters and acceleration feedback parameter by adding muscle activation in combination with activation dynamics and acceleration feedback to the fitted model. From the simulated data, the mDIFF of the basic parameters varied from 22.2–22.4% when estimated using the torque and body sway sensitivity functions. Adding the activation dynamics, acceleration feedback and muscle activation improved mDIFF to 13.1–15.1%. Conclusions Adding the muscle activation in combination with the activation dynamics and acceleration feedback to CLSIT improves the accuracy and reliability of the estimated parameters and gives the possibility to separate the neural time delay, electromechanical delay and the intrinsic and reflexive dynamics. To diagnose impaired balance more specifically, it is recommended to add electromyography (EMG) to body sway (with or without torque) measurements in the assessment of the underlying systems. |
topic |
Posture Human balance control Modelling Muscle activation Activation dynamics |
url |
http://link.springer.com/article/10.1186/s12984-017-0299-x |
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