Low‐dimensional embeddings for interaction design

Rusu, M. M., Schött, S. Y., Williamson, J. H. , Schmidt, A. and Murray-Smith, R. (2022) Low‐dimensional embeddings for interaction design. Advanced Intelligent Systems, 4(2), 2100045. (doi: 10.1002/aisy.202100045)

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Physical interactions with the real world have many degrees of freedom, which has led to the development of novel input devices with a multitude of sensors to capture increasingly high‐dimensional data. This high dimensionality makes the design of interactive systems more complex. Herein, the use of autoencoder‐based dimensionality reduction is explored to simplify the design process. For this purpose, a data glove equipped with accelerometers is used to record high‐dimensional hand movement data that are thereafter reduced to 2D embeddings using autoencoders. The exploration and evaluation of the resulting embeddings suggest that autoencoders can be used to create meaningful low‐dimensional representations of complex human movement. The characteristics generality, variability, connectivity, and distinguishability are established and a guideline is provided for assessing low‐dimensional embeddings. Referring to these characteristics, system engineers can evaluate different input modalities and gestures for their specific interaction task. Further, a framework is outlined for designing and evaluating gesture interaction in the low‐dimensional space. By demonstrating the exemplary design of the interaction with a virtual lever, this research gives system engineers a template for interaction design in the low‐dimensional space.

Item Type:Articles
Keywords:Autoencoders, data gloves, dimensionality reduction, embedding, interaction.
Glasgow Author(s) Enlighten ID:Murray-Smith, Professor Roderick and Williamson, Dr John
Authors: Rusu, M. M., Schött, S. Y., Williamson, J. H., Schmidt, A., and Murray-Smith, R.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:Advanced Intelligent Systems
ISSN (Online):2640-4567
Published Online:27 July 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in Advanced Intelligent Systems 4(2): 2100045
Publisher Policy:Reproduced under a Creative Commons licence

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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
190841UK Quantum Technology Hub in Enhanced Quantum ImagingMiles PadgettEngineering and Physical Sciences Research Council (EPSRC)EP/M01326X/1P&S - Physics & Astronomy
305567QuantIC - The UK Quantum Technoogy Hub in Quantum Enhanced ImagingMiles PadgettEngineering and Physical Sciences Research Council (EPSRC)EP/T00097X/1P&S - Physics & Astronomy