Direct fit of a theoretical model of phase transition in oscillatory finger motions

Peter C.M. Molenaar, Karl M. Newell

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

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 α and β parameters in the SHK model. Comparison between transition onset time and the time at which |β(t | T)/α(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.

Original languageEnglish (US)
Pages (from-to)199-214
Number of pages16
JournalBritish Journal of Mathematical and Statistical Psychology
Volume56
Issue number2
DOIs
StatePublished - Nov 1 2003

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Arts and Humanities (miscellaneous)
  • Psychology(all)

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