Similar sensorimotor transformations control balance during standing and walking.
Standing and walking balance control in humans relies on the transformation of sensory information to motor commands that drive muscles. Here, we evaluated whether sensorimotor transformations underlying walking balance control can be described by task-level center of mass kinematics feedback simila...
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2021-06-01
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Series: | PLoS Computational Biology |
Online Access: | https://doi.org/10.1371/journal.pcbi.1008369 |
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doaj-44db99e0281345f39b4c58161ead66672021-07-22T04:32:42ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582021-06-01176e100836910.1371/journal.pcbi.1008369Similar sensorimotor transformations control balance during standing and walking.Maarten AfschriftFriedl De GrooteIlse JonkersStanding and walking balance control in humans relies on the transformation of sensory information to motor commands that drive muscles. Here, we evaluated whether sensorimotor transformations underlying walking balance control can be described by task-level center of mass kinematics feedback similar to standing balance control. We found that delayed linear feedback of center of mass position and velocity, but not delayed linear feedback from ankle angles and angular velocities, can explain reactive ankle muscle activity and joint moments in response to perturbations of walking across protocols (discrete and continuous platform translations and discrete pelvis pushes). Feedback gains were modulated during the gait cycle and decreased with walking speed. Our results thus suggest that similar task-level variables, i.e. center of mass position and velocity, are controlled across standing and walking but that feedback gains are modulated during gait to accommodate changes in body configuration during the gait cycle and in stability with walking speed. These findings have important implications for modelling the neuromechanics of human balance control and for biomimetic control of wearable robotic devices. The feedback mechanisms we identified can be used to extend the current neuromechanical models that lack balance control mechanisms for the ankle joint. When using these models in the control of wearable robotic devices, we believe that this will facilitate shared control of balance between the user and the robotic device.https://doi.org/10.1371/journal.pcbi.1008369 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maarten Afschrift Friedl De Groote Ilse Jonkers |
spellingShingle |
Maarten Afschrift Friedl De Groote Ilse Jonkers Similar sensorimotor transformations control balance during standing and walking. PLoS Computational Biology |
author_facet |
Maarten Afschrift Friedl De Groote Ilse Jonkers |
author_sort |
Maarten Afschrift |
title |
Similar sensorimotor transformations control balance during standing and walking. |
title_short |
Similar sensorimotor transformations control balance during standing and walking. |
title_full |
Similar sensorimotor transformations control balance during standing and walking. |
title_fullStr |
Similar sensorimotor transformations control balance during standing and walking. |
title_full_unstemmed |
Similar sensorimotor transformations control balance during standing and walking. |
title_sort |
similar sensorimotor transformations control balance during standing and walking. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Computational Biology |
issn |
1553-734X 1553-7358 |
publishDate |
2021-06-01 |
description |
Standing and walking balance control in humans relies on the transformation of sensory information to motor commands that drive muscles. Here, we evaluated whether sensorimotor transformations underlying walking balance control can be described by task-level center of mass kinematics feedback similar to standing balance control. We found that delayed linear feedback of center of mass position and velocity, but not delayed linear feedback from ankle angles and angular velocities, can explain reactive ankle muscle activity and joint moments in response to perturbations of walking across protocols (discrete and continuous platform translations and discrete pelvis pushes). Feedback gains were modulated during the gait cycle and decreased with walking speed. Our results thus suggest that similar task-level variables, i.e. center of mass position and velocity, are controlled across standing and walking but that feedback gains are modulated during gait to accommodate changes in body configuration during the gait cycle and in stability with walking speed. These findings have important implications for modelling the neuromechanics of human balance control and for biomimetic control of wearable robotic devices. The feedback mechanisms we identified can be used to extend the current neuromechanical models that lack balance control mechanisms for the ankle joint. When using these models in the control of wearable robotic devices, we believe that this will facilitate shared control of balance between the user and the robotic device. |
url |
https://doi.org/10.1371/journal.pcbi.1008369 |
work_keys_str_mv |
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