Understanding the variability of pointing tasks with event-driven intermittent control

Alvarez-Martin, J. A. , Doublein, T., Gollee, H. , Müller, J. and Murray-Smith, R. (2022) Understanding the variability of pointing tasks with event-driven intermittent control. IFAC-PapersOnLine, 55(30), pp. 323-328. (doi: 10.1016/j.ifacol.2022.11.073)

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Abstract

Event-driven Intermittent control (IC) has been used as a framework to explain relevant aspects of human movement. The events, which are generated by states crossing predefined thresholds, give rise to state trajectories that mimic those of a continuous controller, by only using feedback information at event times. Here we present the results of using an optimisation approach to identify the parameters of an intermittent controller from experimental data, where users performed one dimensional mouse movements in a reciprocal pointing task. The results show that IC is able to reproduce both, the dynamical features and the variability of the pointing task across participants. We then introduce probabilistic elements in the IC framework in the form of Gaussian processes as an additional method to represent human movement variability.

Item Type:Articles
Additional Information:Funding support provided by EPSRC through grant EP/R018634/1 (Closedloop Data Science) and a PhD Scholarship.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Murray-Smith, Professor Roderick and Doublein, Mr Thomas and Gollee, Dr Henrik and Alvarez Martin, Mr Alberto
Authors: Alvarez-Martin, J. A., Doublein, T., Gollee, H., Müller, J., and Murray-Smith, R.
College/School:College of Science and Engineering > School of Computing Science
College of Science and Engineering > School of Engineering
College of Science and Engineering > School of Engineering > Biomedical Engineering
Journal Name:IFAC-PapersOnLine
Publisher:Elsevier
ISSN:2405-8963
ISSN (Online):2405-8963
Published Online:23 November 2022
Copyright Holders:Copyright © 2022 The Authors
First Published:First published in IFAC-PapersOnLine 55(30): 323-328
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
300982Exploiting Closed-Loop Aspects in Computationally and Data Intensive AnalyticsRoderick Murray-SmithEngineering and Physical Sciences Research Council (EPSRC)EP/R018634/1Computing Science