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

Biological cybernetics
James L Patton, F A Mussa-Ivaldi

Abstract

This study presents a computational framework that capitalizes on known human neuromechanical characteristics during limb movements in order to predict human-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 the 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. The mixture of nonlinear models accounted for 79 +/- 11% (mean +/- SD) of the variance in measured force, and force errors were 0.73 +/- 0.20% of the maximum exerted force. Solutions were acquired in half the time with a significantly better fit. However, both approaches suffered equally from the simplifying assumptions, namely that the human neuromechanical system consisted of a feedforward controller coupled with linear impedanc...Continue Reading

Citations

Apr 1, 2010·Biological cybernetics·Andreas G Fleischer
Jun 12, 2003·Trends in Neurosciences·Ferdinando A Mussa-Ivaldi, Lee E Miller
Mar 7, 2003·Human Movement Science·Asim Ghous, Peter D Neilson
Jan 24, 2007·Assistive Technology : the Official Journal of RESNA·James PattonRobert Kenyon
Nov 16, 2004·Human Movement Science·Peter D Neilson, Megan D Neilson
Apr 9, 2005·IEEE Transactions on Neural Systems and Rehabilitation Engineering : a Publication of the IEEE Engineering in Medicine and Biology Society·Jeremy L Emken, David J Reinkensmeyer
Jan 25, 2006·Behavioural Brain Research·Thierry PozzoNatale Stucchi
Jun 25, 2015·Experimental Brain Research·Zachary A WrightJames L Patton
Jul 17, 2004·Annual Review of Biomedical Engineering·David J ReinkensmeyerSteven C Cramer
Mar 1, 2003·Experimental Brain Research·Craig D Takahashi, David J Reinkensmeyer

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