Human motion capture for movement limitation analysis using an RGB-D camera in spondyloarthritis: a validation study

Manuel Trinidad-Fernández, Antonio Cuesta-Vargas, Peter Vaes, David Beckwée, Francisco Ángel Moreno, Javier González-Jiménez, Antonio Fernández-Nebro, Sara Manrique-Arija, Inmaculada Ureña-Garnica, Manuel González-Sánchez

Research output: Contribution to journalArticle

Abstract

A human motion capture system using an RGB-D camera could be a good option to understand the trunk limitations in spondyloarthritis. The aim of this study is to validate a human motion capture system using an RGB-D camera to analyse trunk movement limitations in spondyloarthritis patients. Cross-sectional study was performed where spondyloarthritis patients were diagnosed with a rheumatologist. The RGB-D camera analysed the kinematics of each participant during seven functional tasks based on rheumatologic assessment. The OpenNI2 library collected the depth data, the NiTE2 middleware detected a virtual skeleton and the MRPT library recorded the trunk positions. The gold standard was registered using an inertial measurement unit. The outcome variables were angular displacement, angular velocity and lineal acceleration of the trunk. Criterion validity and the reliability were calculated. Seventeen subjects (54.35 (11.75) years) were measured. The Bending task obtained moderate results in validity (r = 0.55–0.62) and successful results in reliability (ICC = 0.80–0.88) and validity and reliability of angular kinematic results in Chair task were moderate and (r = 0.60–0.74, ICC = 0.61–0.72). The kinematic results in Timed Up and Go test were less consistent. The RGB-D camera was documented to be a reliable tool to assess the movement limitations in spondyloarthritis depending on the functional tasks: Bending task. Chair task needs further research and the TUG analysis was not validated. Graphical abstract: Comparation of both systems, required software for camera analysis, outcomes and final results of validity and reliability of each test. [Figure not available: see fulltext.]

Original languageEnglish
Pages (from-to)2127-2137
Number of pages11
JournalMedical and Biological Engineering and Computing
Volume59
Issue number10
DOIs
Publication statusPublished - Oct 2021

Keywords

  • BASFI
  • Camera
  • Motion capture
  • Spinal mobility
  • Spondyloarthritis

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