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Submovements are hypothesized building blocks of human movement, discrete ballistic movements of which more complex movements are composed. Using a novel algorithm, submovements were extracted from the point-to-point movements of 41 persons recovering from stroke. Analysis of the extracted submovements showed that, over the course of therapy, patients' submovements tended to increase in peak speed and duration. The number of submovements employed to produce a given movement decreased. The time between the peaks of adjacent submovements decreased for inpatients (those less than 1 month post-stroke), but not for outpatients (those greater than 12 months post-stroke) as a group. Submovements became more overlapped for all patients, but more markedly for inpatients. The strength and consistency with which it quantified patients' recovery indicates that analysis of submovement overlap might be a useful tool for measuring learning or other changes in motor behavior in future human movement studies.
Rohrer is with the Special Projects Group, Intelligent Systems and Robotics Center, Sandia National Laboratories, Albuquerque, NM 87185-1010. Fasoli, Krebs, and Hogan are with the Dept of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139; Hogan is also with the Dept of Brain and Cognitive Science at MIT. Volpe and Krebs are with Dept of Neurology and Neuroscience, Weill Medical College of Cornell University, White Plains, NY 10605. Frontera and Stein are with the Dept of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital/Harvard Medical School, Boston, MA 02114.