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Updated: Feb 20, 2026

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
Published on: January 18, 2020
Camera pose estimation to improve accuracy and reliability of joint angles assessed with attitude and heading
Karina Lebel1, Mathieu Hamel2, Christian Duval3
1Université de Sherbrooke, Faculty of Medicine and Health Sciences, Orthopedic Service, Department of Surgery, 3001, 12e Avenue Nord, Sherbrooke, Québec J1H 5N4, Canada; Research Center on Aging, 1036, Belvédère Sud, Sherbrooke, Quebec J1H 4C4, Canada; Interdisciplinary Institute for Technological Innovation (3IT), Université de Sherbrooke, Faculty of Engineering, 3000 Université Blvd., Sherbrooke, Quebec J1K 0A5, Canada.
Abstract:
Joint kinematics can be assessed using orientation estimates from Attitude and Heading Reference Systems (AHRS). However, magnetically-perturbed environments affect the accuracy of the estimated orientations. This study investigates, both in controlled and human mobility conditions, a trial calibration technic based on a 2D photograph with a pose estimation algorithm to correct initial difference in AHRS Inertial reference frames and improve joint angle accuracy. In controlled conditions, two AHRS were solidly affixed onto a wooden stick and a series of static and dynamic trials were performed in varying environments. Mean accuracy of relative orientation between the two AHRS was improved from 24.4° to 2.9° using the proposed correction method. In human conditions, AHRS were placed on the shank and the foot of a participant who performed repeated trials of straight walking and walking while turning, varying the level of magnetic perturbation in the starting environment and the walking speed. Mean joint orientation accuracy went from 6.7° to 2.8° using the correction algorithm. The impact of starting environment was also greatly reduced, up to a point where one could consider it as non-significant from a clinical point of view (maximum mean difference went from 8° to 0.6°). The results obtained demonstrate that the proposed method improves significantly the mean accuracy of AHRS joint orientation estimations in magnetically-perturbed environments and can be implemented in post processing of AHRS data collected during biomechanical evaluation of motion.
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