Sep 19, 2013

Webinar: Measuring and Incorporating Subject-Specific Muscle Parameters in Post-Stroke Gait Simulations

Jill Higginson, Brian Knarr, and John Ramsay of the University of Delaware describe how subject-specific muscle properties impact simulations of post-stroke gait.

Miss This Event?

You can view a recording of this event here. You can learn more through the following articles:

"Paretic muscle atrophy and non-contractile tissue content in individual muscles of the post-stroke lower extremity," J Biomech, Nov 10, 2011, 44(16):2741-2746.

"Muscle volume as a predictor of maximum force generating ability in the plantar flexors post-stroke," Muscle Nerve, Mar 14, 2013.

"Using submaximal contractions to predict the maximum force-generating ability of muscles," Muscle Nerve, Jun 2012, 45(6):849-858.

"Validation of an adjustment equation for the burst superimposition technique in subjects post-stroke," Muscle Nerve, Aug 2012, 46(2): 267-269.

Details

Title: Measuring and Incorporating Subject-Specific Muscle Parameters in Post-Stroke Gait Simulations
Speakers: Jill Higginson, Brian Knarr, John Ramsay
University of Delaware
Time: Thursday, September 19, 2013 at 9:30 a.m. Pacific Daylight Time

Abstract

Individuals post-stroke often experience abnormal timing and magnitude of muscle activation as well as altered muscle force generating capacity. When generating musculoskeletal models of post-stroke individuals, it is necessary to determine whether the inclusion of subject-specific properties will have a meaningful influence on model results when compared to generic muscle properties. In this webinar, we will discuss our use of experimental and imaging data to guide the development of subject-specific simulations. In particular, we will describe our processes for evaluating the maximum isometric force and volitional activation of major muscle groups of the lower limb in stroke survivors and our process of integrating this data into OpenSim models. We have found that inclusion of subject-specific muscle data when modeling post-stroke gait results in appreciable changes in the model predicted force and activation. Importantly, the observed changes in model results agree with commonly observed compensation patterns in stroke survivors, including increased hip and knee flexor activity and decreased plantar flexor and dorsiflexor activity. Ultimately we hope to use the inclusion of subject-specific data into musculoskeletal models to improve the relevance of our modeling results and enhance the design and outcomes of future rehabilitation.

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