title: Modeling isometric force response using fuzzy set theory.
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 evaluate dynamic system models of isometric force based on fuzzy set theory. The experiments involved subjects exerting isometric force over a range from 5% to 95% of maximal voluntary contraction. The finding suggests that the fuzzy dynamic system model outperforms best fits that were obtained using nonlinear difference equations of higher order.
authors.affiliation: Applied Research Laboratory, The Pennsylvania State University, University Park, PA 16802, USA. JStitt@psu.edu
authors.forename: Joseph P
authors.initials: JP
authors.lastname: Stitt
authors.forename: Karl M
authors.initials: KM
authors.lastname: Newell
mesh_terms: D000328:Adult; D003198:Computer Simulation; D005260:Female; D017143:Fuzzy Logic; D006801:Humans; D007537:Isometric Contraction / Q000502:physiology*; D008297:Male; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000502:physiology*; D010807:Physical Endurance / Q000502:physiology*; D005082:Physical Exertion / Q000502:physiology*; D013314:Stress, Mechanical