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Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures

Integrating mobile eye tracking and optoelectronic motion capture enables point of gaze to be expressed within the laboratory co-ordinate system and presents a method not commonly applied during research examining dynamic behaviors, such as locomotion. This paper examines the quality of gaze data co...

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Detalles Bibliográficos
Autores principales: Hunt, Rhys, Blackmore, Tim, Mills, Chris, Dicks, Matt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516427/
https://www.ncbi.nlm.nih.gov/pubmed/36186610
http://dx.doi.org/10.1177/20416695221116652
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author Hunt, Rhys
Blackmore, Tim
Mills, Chris
Dicks, Matt
author_facet Hunt, Rhys
Blackmore, Tim
Mills, Chris
Dicks, Matt
author_sort Hunt, Rhys
collection PubMed
description Integrating mobile eye tracking and optoelectronic motion capture enables point of gaze to be expressed within the laboratory co-ordinate system and presents a method not commonly applied during research examining dynamic behaviors, such as locomotion. This paper examines the quality of gaze data collected through the integration. Based on research suggesting increased viewing distances are associated with reduced data quality; the accuracy and precision of gaze data as participants (N = 11) viewed floor-based targets at distances of 1–6 m was investigated. A mean accuracy of 2.55 ± 1.12° was identified, however, accuracy and precision measures (relative to targets) were significantly (p < .05) reduced at greater viewing distances. We then consider if signal processing techniques may improve accuracy and precision, and overcome issues associated with missing data. A 4th-order Butterworth lowpass filter with cut-off frequencies determined via autocorrelation did not significantly improve data quality, however, interpolation via Quintic spline was sufficient to overcome gaps of up to 0.1 s. We conclude the integration of gaze and motion capture presents a viable methodology in the study of human behavior and presents advantages for data collection, treatment, and analysis. We provide considerations for the collection, analysis, and treatment of gaze data that may help inform future methodological decisions.
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spelling pubmed-95164272022-09-29 Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures Hunt, Rhys Blackmore, Tim Mills, Chris Dicks, Matt Iperception Standard Article Integrating mobile eye tracking and optoelectronic motion capture enables point of gaze to be expressed within the laboratory co-ordinate system and presents a method not commonly applied during research examining dynamic behaviors, such as locomotion. This paper examines the quality of gaze data collected through the integration. Based on research suggesting increased viewing distances are associated with reduced data quality; the accuracy and precision of gaze data as participants (N = 11) viewed floor-based targets at distances of 1–6 m was investigated. A mean accuracy of 2.55 ± 1.12° was identified, however, accuracy and precision measures (relative to targets) were significantly (p < .05) reduced at greater viewing distances. We then consider if signal processing techniques may improve accuracy and precision, and overcome issues associated with missing data. A 4th-order Butterworth lowpass filter with cut-off frequencies determined via autocorrelation did not significantly improve data quality, however, interpolation via Quintic spline was sufficient to overcome gaps of up to 0.1 s. We conclude the integration of gaze and motion capture presents a viable methodology in the study of human behavior and presents advantages for data collection, treatment, and analysis. We provide considerations for the collection, analysis, and treatment of gaze data that may help inform future methodological decisions. SAGE Publications 2022-09-26 /pmc/articles/PMC9516427/ /pubmed/36186610 http://dx.doi.org/10.1177/20416695221116652 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Standard Article
Hunt, Rhys
Blackmore, Tim
Mills, Chris
Dicks, Matt
Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures
title Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures
title_full Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures
title_fullStr Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures
title_full_unstemmed Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures
title_short Evaluating the integration of eye-tracking and motion capture technologies: Quantifying the accuracy and precision of gaze measures
title_sort evaluating the integration of eye-tracking and motion capture technologies: quantifying the accuracy and precision of gaze measures
topic Standard Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9516427/
https://www.ncbi.nlm.nih.gov/pubmed/36186610
http://dx.doi.org/10.1177/20416695221116652
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