Identifying human postural dynamics and control from unperturbed balance

Abstract Background Upright standing requires control of an inherently unstable multi-joint human body within a small base of support, despite biological motor and / or sensory noise which challenge balance. Without applying perturbations, system ide...

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Main Authors: Lee, Jongwoo, Zhang, Kuangen, Hogan, Neville
Other Authors: Massachusetts Institute of Technology. Department of Mechanical Engineering
Format: Article
Language:English
Published: BioMed Central 2021
Online Access:https://hdl.handle.net/1721.1/132087
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author Lee, Jongwoo
Zhang, Kuangen
Hogan, Neville
author2 Massachusetts Institute of Technology. Department of Mechanical Engineering
author_facet Massachusetts Institute of Technology. Department of Mechanical Engineering
Lee, Jongwoo
Zhang, Kuangen
Hogan, Neville
author_sort Lee, Jongwoo
collection MIT
description Abstract Background Upright standing requires control of an inherently unstable multi-joint human body within a small base of support, despite biological motor and / or sensory noise which challenge balance. Without applying perturbations, system identification methods have been regarded as inadequate, because the relevant internal biological noise processes are not accessible to direct measurement. As a result, unperturbed balance studies have been limited to investigation of behavioral patterns rather than possible underlying control strategies. Methods In this paper, we present a mathemathically rigorous system identification method that is applicable to study the dynamics and control of unperturbed balance. The method is derived from autocorrelation matrices with non-zero time lags and identifies the system matrix of a discrete-time dynamic system in the presence of unknown noise processes, without requiring any information about the strength of the noise. Results Unlike reasonable ‘least-squares’ approaches, the performance of the new method is consistent across a range of different combinations of internal and measurement noise strengths, even when measurement noise is substantial. We present a numerical example of a model that simulates human upright balancing and show that its dynamics can be identified accurately. With a biomechanically reasonable choice of state and input variables, a state feedback controller can also be identified. Conclusions This study provides a new method to correctly identify the dynamics of human standing without the need for known external perturbations. The method was numerically validated using simulation that included realistic features of human balance. This method avoids potential issues of adaptation or possible reflex responses evoked by external perturbations, and does not require expensive in-lab, high-precision measurement equipment. It may eventually enable diagnosis and treatment of individuals with impaired balance, and the development of safe and effective assistive and / or rehabilitative technologies.
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spelling mit-1721.1/1320872023-01-10T19:52:50Z Identifying human postural dynamics and control from unperturbed balance Lee, Jongwoo Zhang, Kuangen Hogan, Neville Massachusetts Institute of Technology. Department of Mechanical Engineering Abstract Background Upright standing requires control of an inherently unstable multi-joint human body within a small base of support, despite biological motor and / or sensory noise which challenge balance. Without applying perturbations, system identification methods have been regarded as inadequate, because the relevant internal biological noise processes are not accessible to direct measurement. As a result, unperturbed balance studies have been limited to investigation of behavioral patterns rather than possible underlying control strategies. Methods In this paper, we present a mathemathically rigorous system identification method that is applicable to study the dynamics and control of unperturbed balance. The method is derived from autocorrelation matrices with non-zero time lags and identifies the system matrix of a discrete-time dynamic system in the presence of unknown noise processes, without requiring any information about the strength of the noise. Results Unlike reasonable ‘least-squares’ approaches, the performance of the new method is consistent across a range of different combinations of internal and measurement noise strengths, even when measurement noise is substantial. We present a numerical example of a model that simulates human upright balancing and show that its dynamics can be identified accurately. With a biomechanically reasonable choice of state and input variables, a state feedback controller can also be identified. Conclusions This study provides a new method to correctly identify the dynamics of human standing without the need for known external perturbations. The method was numerically validated using simulation that included realistic features of human balance. This method avoids potential issues of adaptation or possible reflex responses evoked by external perturbations, and does not require expensive in-lab, high-precision measurement equipment. It may eventually enable diagnosis and treatment of individuals with impaired balance, and the development of safe and effective assistive and / or rehabilitative technologies. 2021-09-20T17:41:53Z 2021-09-20T17:41:53Z 2021-03-22 2021-03-28T04:51:33Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/132087 Journal of NeuroEngineering and Rehabilitation. 2021 Mar 22;18(1):54 PUBLISHER_CC en https://doi.org/10.1186/s12984-021-00843-1 Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf BioMed Central BioMed Central
spellingShingle Lee, Jongwoo
Zhang, Kuangen
Hogan, Neville
Identifying human postural dynamics and control from unperturbed balance
title Identifying human postural dynamics and control from unperturbed balance
title_full Identifying human postural dynamics and control from unperturbed balance
title_fullStr Identifying human postural dynamics and control from unperturbed balance
title_full_unstemmed Identifying human postural dynamics and control from unperturbed balance
title_short Identifying human postural dynamics and control from unperturbed balance
title_sort identifying human postural dynamics and control from unperturbed balance
url https://hdl.handle.net/1721.1/132087
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AT zhangkuangen identifyinghumanposturaldynamicsandcontrolfromunperturbedbalance
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