Direct fit of a theoretical model of phase transition in oscillatory finger motions.
This paper presents a general method to fit the Schöner-Haken-Kelso (SHK) model of human movement phase transitions directly to time series data. A robust variant of the extended Kalman filter technique is applied to the data of a single subject. The options of covariance resetting and iteration within recursion were used to obtain time-dependent estimates of both the alpha and beta parameters in the SHK model. Comparison between transition onset time and the time at which /beta(t/T)/alpha(t/T)/ becomes critical indicates that the transitions are advanced by noise. The method can be extended to handle non-normal data and generalization across subjects and/or experimental conditions.
Molenaar
Peter C M
PC
Department of Psychology, University of Amsterdam, The Netherlands. op_molenaar@macmail.psy.uva.nl
Newell
Karl M
KM
D000328:Adult; D000465:Algorithms; D005385:Fingers; D006801:Humans; D015233:Models, Statistical; D009043:Motor Activity; D017711:Nonlinear Dynamics; D009991:Oscillometry / Q000706:statistics & numerical data*