Validating model-based prediction of biological knee moment during walking with an exoskeleton in crouch gait: Potential application for exoskeleton control

Ji Chen, Diane L. Damiano, Zachary F. Lerner, Thomas C. Bulea

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Advanced control strategies that can adjust assistance based volitional effort from the user may be beneficial for deploying exoskeletons for overground gait training in ambulatory populations, such as children with cerebral palsy (CP). In this study, we evaluate the ability to predict biological knee moment during stance phase of walking with an exoskeleton in two children subjects with crouch gait from CP. The predictive model characterized the knee as a rotational spring with the addition of correction factors at knee extensor moment extrema to predict the instantaneous knee moment profile from the knee angle. Our model prediction performance was comparable to previous studies for weight acceptance (WA) and mid-stance (MS) phases in both assisted (Assist) and non-assisted (Zero) modes based on normalized root mean square error (RMSE), demonstrating the feasibility of joint moment estimation during exoskeleton walking. RMSE was highest in late stance phase, likely due to the non-linear knee stiffness exhibited during this phase in one participant. Overall, our results support real-time implementation of the joint moment prediction model for control of exoskeleton knee extension assistance in children with CP.

Original languageEnglish (US)
Title of host publication2019 IEEE 16th International Conference on Rehabilitation Robotics, ICORR 2019
PublisherIEEE Computer Society
Pages778-783
Number of pages6
ISBN (Electronic)9781728127552
DOIs
StatePublished - Jun 2019
Externally publishedYes
Event16th IEEE International Conference on Rehabilitation Robotics, ICORR 2019 - Toronto, Canada
Duration: Jun 24 2019Jun 28 2019

Publication series

NameIEEE International Conference on Rehabilitation Robotics
Volume2019-June
ISSN (Print)1945-7898
ISSN (Electronic)1945-7901

Conference

Conference16th IEEE International Conference on Rehabilitation Robotics, ICORR 2019
Country/TerritoryCanada
CityToronto
Period6/24/196/28/19

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Rehabilitation
  • Electrical and Electronic Engineering

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