Literature DB >> 25282075

A comparison of static and dynamic optimization muscle force predictions during wheelchair propulsion.

Melissa M Morrow1, Jeffery W Rankin2, Richard R Neptune3, Kenton R Kaufman4.   

Abstract

The primary purpose of this study was to compare static and dynamic optimization muscle force and work predictions during the push phase of wheelchair propulsion. A secondary purpose was to compare the differences in predicted shoulder and elbow kinetics and kinematics and handrim forces. The forward dynamics simulation minimized differences between simulated and experimental data (obtained from 10 manual wheelchair users) and muscle co-contraction. For direct comparison between models, the shoulder and elbow muscle moment arms and net joint moments from the dynamic optimization were used as inputs into the static optimization routine. RMS errors between model predictions were calculated to quantify model agreement. There was a wide range of individual muscle force agreement that spanned from poor (26.4% Fmax error in the middle deltoid) to good (6.4% Fmax error in the anterior deltoid) in the prime movers of the shoulder. The predicted muscle forces from the static optimization were sufficient to create the appropriate motion and joint moments at the shoulder for the push phase of wheelchair propulsion, but showed deviations in the elbow moment, pronation-supination motion and hand rim forces. These results suggest the static approach does not produce results similar enough to be a replacement for forward dynamics simulations, and care should be taken in choosing the appropriate method for a specific task and set of constraints. Dynamic optimization modeling approaches may be required for motions that are greatly influenced by muscle activation dynamics or that require significant co-contraction.
Copyright © 2014 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Biomechanics; Forward dynamics; Musculoskeletal model; Upper extremity

Mesh:

Year:  2014        PMID: 25282075      PMCID: PMC4254308          DOI: 10.1016/j.jbiomech.2014.09.013

Source DB:  PubMed          Journal:  J Biomech        ISSN: 0021-9290            Impact factor:   2.712


  26 in total

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