Robot-based assessment of motor and proprioceptive function identifies biomarkers for prediction of functional independence measures.

Journal: Journal of neuroengineering and rehabilitation
Published Date:

Abstract

BACKGROUND: Neurological impairments following stroke impact the ability of individuals to perform daily activities, although the relative impact of individual impairments is not always clear. Recovery of sensorimotor function following stroke can vary widely, from complete recovery to modest or minimal improvements, across individuals. An important question is whether one can predict the amount of recovery based on initial examination of the individual. Robotic technologies are now being used to quantify a range of behavioral capabilities of individuals post-stroke, providing a rich set of biomarkers of sensory and motor dysfunction. The objective of the present study is to use mathematical models to identify which biomarkers best predict the ability of subjects with stroke to perform daily activities before and after rehabilitation.

Authors

  • Sayyed Mostafa Mostafavi
    School of Computing, Queen's University, Kingston, ON, Canada.
  • Parvin Mousavi
    Medical Informatics Laboratory, School of Computing, Queen's University, 557 Goodwin Hall, Kingston, ON K7L 2N8, Canada.
  • Sean P Dukelow
    Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
  • Stephen H Scott
    Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Ontario, Canada. steve.scott@queensu.ca.