Changes in Predicted Muscle Coordination with Subject-Specific Muscle Parameters for Individuals after Stroke. (24th June 2014)

• Record Type: Journal Article
• Authors: Knarr, Brian A.; Reisman, Darcy S.; Binder-Macleod, Stuart A.; Higginson, Jill S.
• Other Names: Kautz Steve Academic Editor.
• Is Part Of: Stroke research and treatment. Volume 2014(2014)
• Publication Date: 2014-06-24
• Subjects: Cerebrovascular disease -- Periodicals; Stroke; Cerebrovascular Disorders; Cerebrovascular disease; Periodicals; Periodicals; Fulltext; Internet Resources; Periodicals; 616.81
• DOI: 10.1155/2014/321747
• Languages: English
• ISSNs: 2090-8105

Abstract

Abstract : Muscle weakness is commonly seen in individuals after stroke, characterized by lower forces during a maximal volitional contraction. Accurate quantification of muscle weakness is paramount when evaluating individual performance and response to after stroke rehabilitation. The objective of this study was to examine the effect of subject-specific muscle force and activation deficits on predicted muscle coordination when using musculoskeletal models for individuals after stroke. Maximum force generating ability and central activation ratio of the paretic plantar flexors, dorsiflexors, and quadriceps muscle groups were obtained using burst superimposition for four individuals after stroke with a range of walking speeds. Two models were created per subject: one with generic and one with subject-specific activation and maximum isometric force parameters. The inclusion of subject-specific muscle data resulted in changes in the model-predicted muscle forces and activations which agree with previously reported compensation patterns and match more closely the timing of electromyography for the plantar flexor and hamstring muscles. This was the first study to create musculoskeletal simulations of individuals after stroke with subject-specific muscle force and activation data. The results of this study suggest that subject-specific muscle force and activation data enhance the ability of musculoskeletal simulations to accurately predict muscle coordination in individuals after stroke.