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A Nonlinear System Model of Isometric Force

Authors: Joseph P. Stitt; Karl M. Newell;

A Nonlinear System Model of Isometric Force

Abstract

The analysis of isometric force may provide early detection of certain types of neuropathology such as Parkinson's disease. Our long term goal is to determine if there are detectable differences between model parameters of healthy and unhealthy individuals. In this study we used system identification techniques to estimate the parameters of dynamic system models of the isometric force exerted by the index finger and focused on a single category of subjects, healthy young adults. The experiments involved subjects exerting isometric force over a range from 5% to 95% of maximal voluntary contraction. The coefficients of the differential equation models depended on the target force level. This finding suggests that a nonlinear dynamic system model provides the best fit for isometric force experiments.

Keywords

Fingers, Nonlinear Dynamics, Isometric Contraction, Humans, Computer Simulation, Stress, Mechanical, Muscle, Skeletal, Models, Biological, Feedback

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
Average
Top 10%
Top 10%
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