NDLI: Recovery of Arm Movement After Stroke

Content Provider	IEEE Xplore Digital Library
Author	Mirbagheri, M.M. Rymer, W.Z.
Copyright Year	2007
Abstract	To characterize the time-course of change in motor impairment, we examined voluntary elbow movement in stroke survivors over a period of one year post-stroke. We quantified several kinematic features of voluntary rapid elbow extension, by measuring the movement trajectory and its derivatives. The subjects were examined five times, at 1-, 2-, 3-, 6- and 12-months post-stroke. The data analyses had two steps. First we used the ";growth mixture"; model to characterize the recovery patterns of these kinematic parameters. Based on the observed measurements over 1 year, we found two classes of recovery patterns for each kinematic parameter. Subjects in class 1 started with a low value for each parameter and these values increased over time, while subjects in class 2 tended to start with higher value and showed widely divergent recovery patterns. Second, we used the logistic regression analysis to predict these recovery patterns based on Fugl Mayer Scale (FMS) of upper extremity measured on the first visit (i.e. 1 month after stroke). Based on the clinical evaluation of motor function (i.e. FMS) within the first month after stroke, these findings enable us to predict the recovery of arm impaired voluntary movement in hemiparetic stroke subjects at different times during the first year, and potentially beyond.
Starting Page	5370
Ending Page	5372
File Size	280431
Page Count	3
File Format	PDF
ISBN	9781424407873
ISSN	1557170X
DOI	10.1109/IEMBS.2007.4353555
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-08-22
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Flexible manufacturing systems Neuromuscular Elbow Kinematics Mechanical factors Recruitment Motion measurement Data analysis Logistics Regression analysis stroke kinematics Fugl-Meyer recovery voluntary movement
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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