Direct t of a theoretical model of phase transition in oscillatory nger motions

This paper presents a general method to Ž t the Schöner–Haken–Kelso (SHK) model of human movement phase transitions directly to time series data. A robust variant of the extended Kalman Ž lter technique is applied to the data of a single subject. The options of covariance resetting and iteration within recursion were used to obtain timedependent estimates of both the a and b parameters in the SHK model. Comparison between transition onset time and the time at which jb(t jT )/a(t jT )j 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.