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Video Movement Analysis Using Smartphones ViMAS: A Pilot Study
07:51

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Accuracy of Monocular Two-Dimensional Pose Estimation Compared With a Reference Standard for Kinematic Multiview

Oskar Stamm1, Anika Heimann-Steinert1

  • 1Geriatrics Research Group, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.

JMIR Mhealth and Uhealth
|December 21, 2020
PubMed
Summary

This study validates a smartphone app for 2D human pose estimation, finding excellent agreement with a reference standard for clinical kinematic analysis. The app offers a viable, accessible alternative to expensive lab-based systems.

Keywords:
2D human pose estimationanalysisclinical practicekinematicsmobilitymotion capturingsmartphone app

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Area of Science:

  • Biomedical Engineering
  • Clinical Biomechanics
  • Medical Technology

Background:

  • Expensive optoelectronic systems are the gold standard for kinematic analysis but are impractical for routine clinical use.
  • Smartphone-based 2D human pose estimation offers a more accessible approach for clinical kinematic analysis.
  • Evaluating the accuracy of these apps is crucial for clinical specialists who rely on valid data.

Purpose of the Study:

  • To assess the accuracy of the Lindera-v2 mobility analysis app for 2D human pose estimation.
  • To compare joint angle measurements from the Lindera-v2 app against a validated reference standard (PanopticStudio Toolbox).
  • To determine the clinical applicability of the Lindera-v2 app based on its accuracy.

Main Methods:

  • Analyzed 10 video sequences using the Lindera-v2 algorithm.
  • Compared 30,000 data pairs per joint (10 joints) between the app and the reference standard.
  • Calculated mean differences, mean absolute error (MAE), and intraclass correlation coefficients (ICC) to quantify accuracy and agreement.
  • Performed cross-correlation analysis to detect temporal lags.

Main Results:

  • The Lindera-v2 app demonstrated excellent agreement with the reference standard, with ICC values ranging from 0.951 to 0.997.
  • Mean angle differences were minimal, with the right hip showing the closest agreement (-0.05°).
  • The algorithm showed no temporal lag, indicating accurate time-series data.

Conclusions:

  • Smartphone-based 2D pose estimation, as exemplified by the Lindera-v2 app, achieves excellent agreement with validated reference standards.
  • The Lindera-v2 algorithm provides accurate kinematic variable assessment with minimal deviations compared to complex systems.
  • This technology presents a promising, accessible tool for clinical mobility analysis.