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...
Main Authors: | , , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
BioMed Central
2021
|
Online Access: | https://hdl.handle.net/1721.1/132087 |
_version_ | 1826216716814778368 |
---|---|
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. |
first_indexed | 2024-09-23T16:52:18Z |
format | Article |
id | mit-1721.1/132087 |
institution | Massachusetts Institute of Technology |
language | English |
last_indexed | 2024-09-23T16:52:18Z |
publishDate | 2021 |
publisher | BioMed Central |
record_format | dspace |
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 |
work_keys_str_mv | AT leejongwoo identifyinghumanposturaldynamicsandcontrolfromunperturbedbalance AT zhangkuangen identifyinghumanposturaldynamicsandcontrolfromunperturbedbalance AT hoganneville identifyinghumanposturaldynamicsandcontrolfromunperturbedbalance |