Presentation
Application of MML to motor skills acquisition
Faculty of Informatics - Papers (Archive)
  • Chao Sun , University of Wollongong
  • Fazel Naghdy , University of Wollongong
  • David A Stirling , University of Wollongong
RIS ID
17772
Publication Date
1-11-2006
Publication Details

This article was originally published as: Sun, C, Naghdy, F & Stirling, D, Application of MML to motor skills acquisition, International Conference on Computational Intelligence for Modelling, Control and Automation 2006 and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, Sydney, November 2006, 77. Copyright IEEE 2006.

Abstract

Study on modeling human psychomotor behaviour based on tracked motion data is reported. The motion data is acquired through various integrated inertial sensors, and represented as Euler angles and accelerations. The Minimum Message Length (MML) algorithm is used to identify frames of intrinsic segmentations and to acquire a classification basis for unsupervised machine learning. The classification model can ultimately be deployed in recognizing certain skilled behaviors. The prior results are analyzed as FSMs' (Finite State Machines) to extract the potential rules underlying behaviors. The progress made so far and plan for further work is reported.

Citation Information
Chao Sun, Fazel Naghdy and David A Stirling. "Application of MML to motor skills acquisition" (2006)
Available at: http://works.bepress.com/fnaghdy/2/