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An Integrated Eye-Tracking and Motion Capture System in Synchronized Gaze and Movement Analysis
KTH, School of Engineering Sciences (SCI), Engineering Mechanics. KTH Move Ability Lab.
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics. KTH Move Ability Lab.ORCID iD: 0000-0002-4679-2934
KTH, School of Engineering Sciences (SCI), Engineering Mechanics. KTH Move Ability Lab.
KTH, School of Engineering Sciences (SCI), Engineering Mechanics, Vehicle Engineering and Solid Mechanics. KTH Move Ability Lab.ORCID iD: 0000-0002-2232-5258
2023 (English)In: 2023 international conference on rehabilitation robotics, ICORR, Institute of Electrical and Electronics Engineers (IEEE) , 2023Conference paper, Published paper (Refereed)
Abstract [en]

Integrating mobile eye-tracking and motion capture emerges as a promising approach in studying visual-motor coordination, due to its capability of expressing gaze data within the same laboratory-centered coordinate system as body movement data. In this paper, we proposed an integrated eye-tracking and motion capture system, which can record and analyze temporally and spatially synchronized gaze and motion data during dynamic movement. The accuracy of gaze measurement were evaluated on five participants while they were instructed to view fixed vision targets at different distances while standing still or walking towards the targets. Similar accuracy could be achieved in both static and dynamic conditions. To demonstrate the usability of the integrated system, several walking tasks were performed in three different pathways. Results revealed that participants tended to focus their gaze on the upcoming path, especially on the downward path, possibly for better navigation and planning. In a more complex pathway, coupled with more gaze time on the pathway, participants were also found having the longest step time and shortest step length, which led to the lowest walking speed. It was believed that the integration of eye-tracking and motion capture is a feasible and promising methodology quantifying visual-motor coordination in locomotion.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) , 2023.
Series
International Conference on Rehabilitation Robotics ICORR, ISSN 1945-7898
Keywords [en]
Visual-motor coordination, eye-tracking, motion capture, gaze behaviour, gait analysis
National Category
Computer graphics and computer vision
Identifiers
URN: urn:nbn:se:kth:diva-341991DOI: 10.1109/ICORR58425.2023.10304692ISI: 001103260000020PubMedID: 37941206Scopus ID: 2-s2.0-85176465911OAI: oai:DiVA.org:kth-341991DiVA, id: diva2:1825262
Conference
International Conference on Rehabilitation Robotics (ICORR), SEP 24-28, 2023, Singapore, SINGAPORE
Note

Part of proceedings ISBN 979-8-3503-4275-8

QC 20240109

Available from: 2024-01-09 Created: 2024-01-09 Last updated: 2025-02-07Bibliographically approved

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Wan, Zhao-YuanLiu, YixingZhang, XiaochenWang, Ruoli

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