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Functional data analytics for kinematic assessments of motor control

August 1, 2016 to May 31, 2021
Funding Status: 
Active Project
Funding Agency: 
National Institutes of Health (NIH)
Funding Institute: 
National Institute of Neurological Disorders and Stroke (NINDS)


We propose to develop models that address gaps in the statistical literature exposed by data produced in experiments using kinematic data to assess motor control, skill, learning, and recovery following stroke. In place of immense data reductions, which are the current standard analysis, we propose a collection of models using a functional data analytic perspective. 


Tomoko's Photo
Lab Director
Human Motor Recovery Laboratory
Assistant Professor

Conditions & Recovery

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Write and walk again.
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Stroke is the leading cause of disability in the U.S.