title: Does EMG control lead to distinct motor adaptation?
abstract: Powered prostheses are controlled using electromyographic (EMG) signals, which may introduce high levels of uncertainty even for simple tasks. According to Bayesian theories, higher uncertainty should influence how the brain adapts motor commands in response to perceived errors. Such adaptation may critically influence how patients interact with their prosthetic devices; however, we do not yet understand adaptation behavior with EMG control. Models of adaptation can offer insights on movement planning and feedback correction, but we first need to establish their validity for EMG control interfaces. Here we created a simplified comparison of prosthesis and able-bodied control by studying adaptation with three control interfaces: joint angle, joint torque, and EMG. Subjects used each of the control interfaces to perform a target-directed task with random visual perturbations. We investigated how control interface and visual uncertainty affected trial-by-trial adaptation. As predicted by Bayesian models, increased errors and decreased visual uncertainty led to faster adaptation. The control interface had no significant effect beyond influencing error sizes. This result suggests that Bayesian models are useful for describing prosthesis control and could facilitate further investigation to characterize the uncertainty faced by prosthesis users. A better understanding of factors affecting movement uncertainty will guide sensory feedback strategies for powered prostheses and clarify what feedback information best improves control.
authors.affiliation: Center for Bionic Medicine, Rehabilitation Institute of Chicago Chicago, IL, USA ; Department of Biomedical Engineering, Northwestern University Evanston, IL, USA.
authors.forename: Reva E
authors.initials: RE
authors.lastname: Johnson
authors.affiliation: Department of Physical Medicine and Rehabilitation, Northwestern University and Rehabilitation Institute of Chicago Chicago, IL, USA ; Department of Engineering Sciences and Applied Mathematics, Northwestern University Evanston, IL, USA ; Department of Physiology, Northwestern University Chicago, IL, USA.
authors.forename: Konrad P
authors.initials: KP
authors.lastname: Kording
authors.affiliation: Center for Bionic Medicine, Rehabilitation Institute of Chicago Chicago, IL, USA ; Department of Biomedical Engineering, Northwestern University Evanston, IL, USA ; Department of Physical Medicine and Rehabilitation, Northwestern University and Rehabilitation Institute of Chicago Chicago, IL, USA.
authors.forename: Levi J
authors.initials: LJ
authors.lastname: Hargrove
authors.affiliation: Department of Physical Medicine and Rehabilitation, Northwestern University and Rehabilitation Institute of Chicago Chicago, IL, USA ; Institute of Biomedical Engineering, University of New Brunswick Fredericton, NB, Canada ; Department of Electrical and Computer Engineering, University of New Brunswick Fredericton, NB, Canada.
authors.forename: Jonathon W
authors.initials: JW
authors.lastname: Sensinger
keywords: EMG; motor adaptation; prosthesis control; sensory feedback; uncertainty