Literature DB >> 33157871

Robot-induced perturbations of human walking reveal a selective generation of motor adaptation.

Iahn Cajigas1, Alexander Koenig1, Giacomo Severini1,2, Maurice Smith3, Paolo Bonato4,5.   

Abstract

The processes underlying the generation of motor adaptation in response to mechanical perturbations during human walking have been subject to debate. We used a robotic system to apply mechanical perturbations to step length and step height over consecutive gait cycles. Specifically, we studied perturbations affecting only step length, only step height, and step length and height in combination. Both step-length and step-height perturbations disrupt normal walking patterns, but step-length perturbations have a far greater impact on locomotor stability. We found a selective process of motor adaptation in that participants failed to adapt to step-height perturbations but strongly adapted to step-length perturbations, even when these adaptations increased metabolic cost. These results indicate that motor adaptation during human walking is primarily driven by locomotor stability, and only secondarily by energy expenditure and walking pattern preservation. These findings have substantial implications for the design of protocols for robot-assisted gait rehabilitation.
Copyright © 2017, American Association for the Advancement of Science.

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Year:  2017        PMID: 33157871     DOI: 10.1126/scirobotics.aam7749

Source DB:  PubMed          Journal:  Sci Robot        ISSN: 2470-9476


  9 in total

1.  Robot-Aided Training of Propulsion During Walking: Effects of Torque Pulses Applied to the Hip and Knee Joints During Stance.

Authors:  Robert McGrath; Barry Bodt; Fabrizio Sergi
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2021-01-28       Impact factor: 3.802

2.  Energy expenditure does not solely explain step length-width choices during walking.

Authors:  Stephen A Antos; Konrad P Kording; Keith E Gordon
Journal:  J Exp Biol       Date:  2022-03-18       Impact factor: 3.312

3.  Manual stabilization reveals a transient role for balance control during locomotor adaptation.

Authors:  Sungwoo Park; James M Finley
Journal:  J Neurophysiol       Date:  2022-08-10       Impact factor: 2.974

Review 4.  Deep reinforcement learning for modeling human locomotion control in neuromechanical simulation.

Authors:  Seungmoon Song; Łukasz Kidziński; Xue Bin Peng; Carmichael Ong; Jennifer Hicks; Sergey Levine; Christopher G Atkeson; Scott L Delp
Journal:  J Neuroeng Rehabil       Date:  2021-08-16       Impact factor: 4.262

5.  Ankle resistance with a unilateral soft exosuit increases plantarflexor effort during pushoff in unimpaired individuals.

Authors:  Krithika Swaminathan; Sungwoo Park; Fouzia Raza; Franchino Porciuncula; Sangjun Lee; Richard W Nuckols; Louis N Awad; Conor J Walsh
Journal:  J Neuroeng Rehabil       Date:  2021-12-27       Impact factor: 4.262

Review 6.  Converging Robotic Technologies in Targeted Neural Rehabilitation: A Review of Emerging Solutions and Challenges.

Authors:  Kostas Nizamis; Alkinoos Athanasiou; Sofia Almpani; Christos Dimitrousis; Alexander Astaras
Journal:  Sensors (Basel)       Date:  2021-03-16       Impact factor: 3.576

7.  Editorial: Somatosensory Integration in Human Movement: Perspectives for Neuromechanics, Modelling and Rehabilitation.

Authors:  Leonardo Gizzi; Ivan Vujaklija; Massimo Sartori; Oliver Röhrle; Giacomo Severini
Journal:  Front Bioeng Biotechnol       Date:  2021-07-14

8.  Learning to walk with a wearable robot in 880 simple steps: a pilot study on motor adaptation.

Authors:  Florian L Haufe; Alessia M Kober; Peter Wolf; Robert Riener; Michele Xiloyannis
Journal:  J Neuroeng Rehabil       Date:  2021-11-01       Impact factor: 4.262

9.  Altered active control of step width in response to mediolateral leg perturbations while walking.

Authors:  Nicholas K Reimold; Holly A Knapp; Rachel E Henderson; Landi Wilson; Alyssa N Chesnutt; Jesse C Dean
Journal:  Sci Rep       Date:  2020-07-22       Impact factor: 4.996

  9 in total

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