Biomedical Engineering Advances (Jun 2024)

Validation of upper extremity kinematics using Markerless motion capture

  • Robyn M. Hansen,
  • Sara L. Arena,
  • Robin M. Queen

Journal volume & issue
Vol. 7
p. 100128

Abstract

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Movement research has typically been performed using three-dimensional (3D) marker-based motion capture, which is considered the “gold-standard” for biomechanical assessment. However, limitations exist due to the lack of portability, extensive preparation for data collection, marker placement training, error due to marker movement, and possible skin irritation due to marker adhesives. There is inherent error due to motion artifact stemming from skin movement and differences in marker placement between testers. Markerless motion capture systems are emerging as a new method of kinematic assessment. These methods require little preparation and there is no need to alter participant clothing. Markerless motion capture has also been validated for the lower extremity in healthy older adults during gait. However, it has not been validated for other populations or for the assessment of upper extremity (UE) motion. Therefore, the purpose of this study was to examine differences in calculated UE kinematics between marker-based and a markerless motion capture system. Participants attended two data collection sessions. Marker-based and markerless motion capture data was collected simultaneously while participants completed the Box and Blocks test (BBT). Kinematic and spatiotemporal data from both systems was exported using identical time series to ensure the same conditions for comparisons. Intraclass Correlation Coefficients (ICCs) were calculated to determine between session reliability for both systems on range of motion and peak joint angular data to ensure movement variability was not affecting measurement consistency. ICCs and Bland Altman statistics were also calculated between the systems. Root mean square deviation (RMSD) values were determined between demeaned UE joint angles for the two systems to examine movement pattern differences. The resulting between-session ICCs for each system showed that the markerless system shared similar reliability during this task as the marker-based system, further supporting the effect of variability on between-session reliability. Between-system ICCs resulted in good (0.70.9) agreement. Bland Altman results confirmed the existence of measurement bias between the systems. RMSD values for all UE joint angles were found to be less than 6°. Overall, the results from this study support the use of markerless motion capture in clinical settings to examine upper extremity biomechanics in children.

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