ArticleJournal of occupational rehabilitation2021
Towards the Use of 2D Video-Based Markerless Motion Capture to Measure and Parameterize Movement During Functional Capacity Evaluation.
Article in Journal of occupational rehabilitation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- User-Centred Design to Inform Requirements for a Remotely Administered Hybrid Functional Test (RAHFT) Protocol.Journal of occupational rehabilitation · 2025Article
- How accurately can we estimate spontaneous body kinematics from video recordings? Effect of movement amplitude on OpenPose accuracy.Behavior research methods · 2025Article
- Evaluation of functional tests performance using a camera-based and machine learning approach.PloS one · 2023Article
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Authors and funding
2 authors at 1 institution in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Purpose The objective of this study was to determine the agreement of kinematic parameters calculated from motion data collected via a 2D video-based pose-estimation (markerless motion capture) approach and a laboratory-based 3D motion capture approach during a floor-to-waist height functional lifting test. Method Twenty healthy participants each performed three floor-to-waist height lifts. Participants' lifts were captured simultaneously using 2D video (camcorder) in the sagittal plane and 3D motion capture (Vicon, Oxford, UK). The three lifts were representative of a perceived light, medium, and heavy load. Post-collection, video data were processed through a pose-estimation software (i.e., markerless motion capture). Motion data from 3D motion capture and video-based markerless motion capture were each used to calculate objective measures of interest relevant to a functional capacity evaluation (i.e., posture, balance, distance of the load from the body, and coordination). Bland-Altman analyses were used to calculate agreement between the two methods. Results Bland-Altman analysis revealed that mean differences ranged from 1.9° to 22.1° for posture and coordination-based metrics calculated using markerless and 3D motion capture, respectively. Limits of agreement for most posture and coordination measures were approximately + 20°. Conclusions 2D video-based pose estimation offers a strategy to objectively measure movement and subsequently calculated metrics of interest within an FCE context and setting, but at present the agreement between metrics calculated using 2D video-based methods and 3D motion capture is insufficient. Therefore, continued effort is required to improve the accuracy of 2D-video based pose estimation prior to inclusion into functional testing paradigms.
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