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- W4247787036 abstract "Chronic spinal cord injury induces musculoskeletal deterioration that can prove to be life threatening. Preliminary work suggests electrically stimulated isometric muscle training may attenuate these detrimental adaptations. Mathematical muscle models would assist in developing the optimal activation strategy to generate various doses of muscle force. However, the accuracy of various muscle models (linear vs nonlinear) have not previously been compared in human paralyzed muscle. PURPOSE To determine the errors associated with three different mathematical muscle modelling approches relative to human chronically paralyzed soleus muscle properties. METHODS Three models of varying complexity (a Hill based nonlinear (NL), a 2nd order NL, and a 2nd order linear model) were parameterized using a variable ramp of increasing and decreasing frequencies for 4 individuals with chronic spinal cord injury (SCI, 2.54 ± 1.26 yrs). Based on these parameter values, 9 trains (5, 10, and 20 Hz constant, CT, doublet, DT, and dual doublet, DDT, trains) and 1 twitch were predicted for each model and compared to the experimental results for each subject (Matlab 6.0). Overall errors (% error, R2, and constant error) as well as specific force property errors (peak force, PF, force time integral, FTI, time to peak tension, TPT, half-relaxation time, HRT, relative fusion index, RFI, doublet PF, DPF, and doublet FTI, DFTI) were calculated. Model comparisons were made using repeated measures ANOVA. RESULTS The Hill-based and 2nd order NL models had different overall force errors (8.1 and 9.9% error, resp.; p=0.0164), but no significant differences for R2, constant error, PF, FTI, RFI, DPF, or DFTI. The simplest linear model, although significantly worse, produced only 15.2% error overall, with the largest errors observed using the 20 Hz DDT pattern (27.7% error). The linear model was equivalent to the best NL models for predicting RFI and TPT. The 2nd order NL model had the largest TPT errors of the three. CONCLUSION Both NL models provide excellent force property predictions for human SCI muscle. The 2nd order NL model, however, is less computationally complex, making it the preferred choice. The linear model, although worse than either NL model overall, provided reasonable force estimates over a limited range of inputs using a very simple modeling approach. Supported by NIH grant RO1 HD39445 (RKS) and The Foundation for Physical Therapy (LFL)." @default.
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- W4247787036 date "2005-05-01" @default.
- W4247787036 modified "2023-09-30" @default.
- W4247787036 title "Predicting Human Paralyzed Soleus Muscle Force Properties Using Three Mathematical Muscle Models" @default.
- W4247787036 doi "https://doi.org/10.1249/00005768-200505001-00193" @default.
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