Efficient human-machine control with asymmetric marginal reliability input devices

Williamson, J. H. , Quek, M., Popescu, I., Ramsay, A. and Murray-Smith, R. (2020) Efficient human-machine control with asymmetric marginal reliability input devices. PLoS ONE, 15(6), e0233603. (doi: 10.1371/journal.pone.0233603) (PMID:32479507) (PMCID:PMC7263597)

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Input devices such as motor-imagery brain-computer interfaces (BCIs) are often unreliable. In theory, channel coding can be used in the human-machine loop to robustly encapsulate intention through noisy input devices but standard feedforward error correction codes cannot be practically applied. We present a practical and general probabilistic user interface for binary input devices with very high noise levels. Our approach allows any level of robustness to be achieved, regardless of noise level, where reliable feedback such as a visual display is available. In particular, we show efficient zooming interfaces based on feedback channel codes for two-class binary problems with noise levels characteristic of modalities such as motor-imagery based BCI, with accuracy <75%. We outline general principles based on separating channel, line and source coding in human-machine loop design. We develop a novel selection mechanism which can achieve arbitrarily reliable selection with a noisy two-state button. We show automatic online adaptation to changing channel statistics, and operation without precise calibration of error rates. A range of visualisations are used to construct user interfaces which implicitly code for these channels in a way that it is transparent to users. We validate our approach with a set of Monte Carlo simulations, and empirical results from a human-in-the-loop experiment showing the approach operates effectively at 50-70% of the theoretical optimum across a range of channel conditions.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Murray-Smith, Professor Roderick and Paun, Ms Iulia and Williamson, Dr John and Ramsay, Mr Andrew
Creator Roles:
Williamson, J.Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Software, Supervision, Visualization, Writing – original draft, Writing – review and editing
Murray-Smith, R.Conceptualization, Funding acquisition, Project administration, Writing – review and editing
Popescu, I.Investigation, Methodology
Ramsay, A.Methodology, Software
Authors: Williamson, J. H., Quek, M., Popescu, I., Ramsay, A., and Murray-Smith, R.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:PLoS ONE
Publisher:Public Library of Science
ISSN (Online):1932-6203
Copyright Holders:Copyright © 2020 The Authors
First Published:First published in PLoS ONE 15(6):e0233603
Publisher Policy:Reproduced under a Creative Commons Licence
Data DOI:10.5525/gla.researchdata.872

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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
160929Tools for Brain Computer InteractionRoderick Murray-SmithEuropean Commission (EC)224631Computing Science
171157MoreGRASPRoderick Murray-SmithEuropean Commission (EC)643955Computing Science