Title :
Modeling isometric force response using Fuzzy Set Theory
Author :
Stitt, J.P. ; Newell, K.M.
Author_Institution :
Pennsylvania State Univ., University Park
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.
Keywords :
biomechanics; diseases; fuzzy set theory; medical computing; neurophysiology; Parkinson´s disease; fuzzy dynamic system model; fuzzy set theory; isometric force response; maximal voluntary contraction; neuropathology; nonlinear difference equations; Difference equations; Fingers; Fuzzy set theory; Fuzzy systems; Nonlinear dynamical systems; Parkinson´s disease; Pathology; Resonance; Resonant frequency; Steady-state; Adult; Computer Simulation; Female; Fuzzy Logic; Humans; Isometric Contraction; Male; Models, Biological; Muscle, Skeletal; Physical Endurance; Physical Exertion; Stress, Mechanical;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4353021