Journal of Applied Physiology Fuel your research with LabChart
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH
 QUICK SEARCH:   [advanced]


     


J Appl Physiol (November 23, 2005). doi:10.1152/japplphysiol.00935.2005
This Article
Right arrow Full Text (PDF) Free
Right arrow All Versions of this Article:
100/3/1027    most recent
00935.2005v1
Right arrow Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when eLetters are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Frey Law, L. A.
Right arrow Articles by Shields, R. K.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Frey Law, L. A.
Right arrow Articles by Shields, R. K.
Submitted on August 2, 2005
Accepted on November 22, 2005

PREDICTING HUMAN CHRONICALLY PARALYZED MUSCLE FORCE: A COMPARISON OF THREE MATHEMATICAL MODELS

Laura A. Frey Law1 and Richard K. Shields1*

1 Graduate Program in Physical Therapy & Rehabilitation Science, The University of Iowa, Iowa City, IA, USA

* To whom correspondence should be addressed. E-mail: richard-shields{at}uiowa.edu.

Chronic spinal cord injury (SCI) induces detrimental musculoskeletal adaptations that adversely effect health status, ranging from muscle paralysis and skin ulcerations to osteoporosis. SCI rehabilitative efforts may increasingly focus on preserving the integrity of paralyzed extremities to maximize health quality using electrical stimulation for isometric training and/or functional activities. Subject-specific mathematical muscle models could prove valuable for predicting the forces necessary to achieve therapeutic loading conditions in individuals with paralyzed limbs. While numerous muscle models are available, three modeling approaches were chosen that can accommodate a variety of stimulation input patterns. To our knowledge no direct comparisons between model comparisons using paralyzed muscle have been reported. The three models include: 1) a simple 2nd order linear model with three parameters and 2) two six-parameter nonlinear models (a 2nd order nonlinear model and a Hill-derived nonlinear model). Soleus muscle forces from four individuals with complete, chronic SCI were used to optimize each model's parameters (using an increasing and decreasing frequency ramp) and to assess the models' predictive accuracies for constant and variable (doublet) stimulation trains at 5, 10, and 20 Hz in each individual. Despite the large differences in modeling approaches, the mean predicted force errors differed only moderately (8-15 % error, p=0.0042), suggesting physiologic force can be adequately represented by multiple mathematical constructs. The two nonlinear models predicted specific force characteristics better than the linear model in nearly all stimulation conditions, with minimal differences between the two nonlinear models. Either nonlinear mathematical model can provide reasonable force estimates; individual application needs may dictate the preferred modeling strategy.




This article has been cited by other articles:


Home page
J. Appl. Physiol.Home page
R. K. Shields, S. Dudley-Javoroski, and K. R. Cole
Feedback-controlled stimulation enhances human paralyzed muscle performance
J Appl Physiol, November 1, 2006; 101(5): 1312 - 1319.
[Abstract] [Full Text] [PDF]


Home page
J. Appl. Physiol.Home page
R. K. Shields, S. Dudley-Javoroski, and A. E. Littmann
Postfatigue potentiation of the paralyzed soleus muscle: evidence for adaptation with long-term electrical stimulation training
J Appl Physiol, August 1, 2006; 101(2): 556 - 565.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH
Visit Other APS Journals Online
Copyright © 1948 by the American Physiological Society.