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2002

Linear combinations of nonlinear models for predicting human-machine interface forces

10 years 1 months ago
Linear combinations of nonlinear models for predicting human-machine interface forces
ACT This study presents a computational framework that capitalizes on known human neuromechanical characteristics during limb movements in order to predict man-machine interactions. A parallel-distributed approach, the mixture of nonlinear models, fits the relationship between the measured kinematics and kinetics at the handle of a robot. Each element of the mixture represented the arm and its controller as a feedforward nonlinear model of inverse dynamics plus a linear approximation of musculotendonous impedance. We evaluated this approach with data from experiments where subjects held a handle of a planar manipulandum robot and attempted to make point-to-point reaching movements. We compared the performance to the more conventional approach of a constrained, nonlinear optimization of the parameters. On average, the mixture of nonlinear models accounted for 0.79
James L. Patton, Ferdinando A. Mussa-Ivaldi
Added 16 Dec 2010
Updated 16 Dec 2010
Type Journal
Year 2002
Where BC
Authors James L. Patton, Ferdinando A. Mussa-Ivaldi
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