Literature DB >> 30500731

Three-dimensional cameras and skeleton pose tracking for physical function assessment: A review of uses, validity, current developments and Kinect alternatives.

Ross A Clark1, Benjamin F Mentiplay2, Emma Hough3, Yong Hao Pua4.   

Abstract

BACKGROUND: Three-dimensional camera systems that integrate depth assessment with traditional two-dimensional images, such as the Microsoft Kinect, Intel Realsense, StereoLabs Zed and Orbecc, hold great promise as physical function assessment tools. When combined with point cloud and skeleton pose tracking software they can be used to assess many different aspects of physical function and anatomy. These assessments have received great interest over the past decade, and will likely receive further study as the integration of depth sensing and augmented reality smartphone cameras occurs more in everyday life. RESEARCH QUESTION: The aim of this review is to discuss how these devices work, what options are available, the best methods for performing assessments and how they can be used in the future.
METHODS: Firstly, a review of the Microsoft Kinect devices and associated artificial intelligence, automated skeleton tracking algorithms is provided. This includes a narrative critique of the validity and clinical utility of these devices for assessing different aspects of physical function including spatiotemporal, kinematic and inverse dynamics data derived from gait and balance trials, and anatomical assessments performed using the depth sensor information. Methods for improving the accuracy of data are examined, including multiple-camera systems and sensor fusion with inertial monitoring units, model fitting, and marker tracking. Secondly, alternative hardware, including other structured light and time of flight methods, stereoscopic cameras and augmented reality leveraging smartphone and tablet cameras to perform measurements in three-dimensional space are summarised. Software options related to depth sensing cameras are then discussed, focussing on recent advances such as OpenPose and web-based methods such as PoseNet. RESULTS AND SIGNIFICANCE: The clinical and non-laboratory utility of these devices holds great promise for physical function assessment, and recent developments could strengthen their ability to provide important and impactful health-related data.
Copyright © 2018 Elsevier B.V. All rights reserved.

Keywords:  Depth camera; Joint angles; Reliability; Validity; Walking; XBox

Mesh:

Year:  2018        PMID: 30500731     DOI: 10.1016/j.gaitpost.2018.11.029

Source DB:  PubMed          Journal:  Gait Posture        ISSN: 0966-6362            Impact factor:   2.840


  23 in total

1.  Expanding instrumented gait testing in the community setting: A portable, depth-sensing camera captures joint motion in older adults.

Authors:  Robert J Dawe; Lei Yu; Sue E Leurgans; Timothy Truty; Thomas Curran; Jeffrey M Hausdorff; Markus A Wimmer; Joel A Block; David A Bennett; Aron S Buchman
Journal:  PLoS One       Date:  2019-05-15       Impact factor: 3.240

2.  Validation of a Single RGB-D Camera for Gait Assessment of Polyneuropathy Patients.

Authors:  Maria do Carmo Vilas-Boas; Ana Patrícia Rocha; Hugo Miguel Pereira Choupina; Márcio Neves Cardoso; José Maria Fernandes; Teresa Coelho; João Paulo Silva Cunha
Journal:  Sensors (Basel)       Date:  2019-11-12       Impact factor: 3.576

3.  Adaptive Rehabilitation Bots in Serious Games.

Authors:  Imad Afyouni; Abdullah Murad; Anas Einea
Journal:  Sensors (Basel)       Date:  2020-12-09       Impact factor: 3.576

4.  Accuracy of Monocular Two-Dimensional Pose Estimation Compared With a Reference Standard for Kinematic Multiview Analysis: Validation Study.

Authors:  Oskar Stamm; Anika Heimann-Steinert
Journal:  JMIR Mhealth Uhealth       Date:  2020-12-21       Impact factor: 4.773

5.  3D Tracking of Human Motion Using Visual Skeletonization and Stereoscopic Vision.

Authors:  Matteo Zago; Matteo Luzzago; Tommaso Marangoni; Mariolino De Cecco; Marco Tarabini; Manuela Galli
Journal:  Front Bioeng Biotechnol       Date:  2020-03-05

6.  A Novel Method of Human Joint Prediction in an Occlusion Scene by Using Low-cost Motion Capture Technique.

Authors:  Jianwei Niu; Xiai Wang; Dan Wang; Linghua Ran
Journal:  Sensors (Basel)       Date:  2020-02-18       Impact factor: 3.576

7.  Validation, Reliability, and Responsiveness Outcomes Of Kinematic Assessment With An RGB-D Camera To Analyze Movement In Subacute And Chronic Low Back Pain.

Authors:  Manuel Trinidad-Fernández; David Beckwée; Antonio Cuesta-Vargas; Manuel González-Sánchez; Francisco-Angel Moreno; Javier González-Jiménez; Erika Joos; Peter Vaes
Journal:  Sensors (Basel)       Date:  2020-01-27       Impact factor: 3.576

8.  Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard: A Pilot Study.

Authors:  Justin Amadeus Albert; Victor Owolabi; Arnd Gebel; Clemens Markus Brahms; Urs Granacher; Bert Arnrich
Journal:  Sensors (Basel)       Date:  2020-09-08       Impact factor: 3.576

9.  Kinect V2-Based Gait Analysis for Children with Cerebral Palsy: Validity and Reliability of Spatial Margin of Stability and Spatiotemporal Variables.

Authors:  Yunru Ma; Kumar Mithraratne; Nichola Wilson; Yanxin Zhang; Xiangbin Wang
Journal:  Sensors (Basel)       Date:  2021-03-17       Impact factor: 3.576

10.  Clinical 3-D Gait Assessment of Patients With Polyneuropathy Associated With Hereditary Transthyretin Amyloidosis.

Authors:  Maria do Carmo Vilas-Boas; Ana Patrícia Rocha; Márcio Neves Cardoso; José Maria Fernandes; Teresa Coelho; João Paulo Silva Cunha
Journal:  Front Neurol       Date:  2020-11-23       Impact factor: 4.086

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