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Article

A Quality Control Check to Ensure Comparability of Stereophotogrammetric Data between Sessions and Systems

1
Department of Mechanical Engineering & INSIGNEO Institute of In Silico Medicine, The University of Sheffield, Sheffield S1 3JD, UK
2
Translational and Clinical Research Institute, Faculty of Medical Science, Newcastle University, Newcastle upon Tyne NE4 5TG, UK
3
Department of Neurology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel University, 24105 Kiel, Germany
4
Centre for the Study of Movement, Cognition and Mobility, Tel Aviv Sourasky Medical Centre, Tel Aviv 6492416, Israel
5
Department for Geriatric Rehabilitation, Robert-Bosch-Hospital, 70376 Stuttgart, Germany
6
Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Torino, Italy
*
Author to whom correspondence should be addressed.
Membership of Mobilise-D consortium is provided in the Acknowledgements.
Academic Editor: Marco Carratù
Sensors 2021, 21(24), 8223; https://doi.org/10.3390/s21248223
Received: 20 October 2021 / Revised: 3 December 2021 / Accepted: 7 December 2021 / Published: 9 December 2021
(This article belongs to the Collection Instrument and Measurement)
Optoelectronic stereophotogrammetric (SP) systems are widely used in human movement research for clinical diagnostics, interventional applications, and as a reference system for validating alternative technologies. Regardless of the application, SP systems exhibit different random and systematic errors depending on camera specifications, system setup and laboratory environment, which hinders comparing SP data between sessions and across different systems. While many methods have been proposed to quantify and report the errors of SP systems, they are rarely utilized due to their complexity and need for additional equipment. In response, an easy-to-use quality control (QC) check has been designed that can be completed immediately prior to a data collection. This QC check requires minimal training for the operator and no additional equipment. In addition, a custom graphical user interface ensures automatic processing of the errors in an easy-to-read format for immediate interpretation. On initial deployment in a multicentric study, the check (i) proved to be feasible to perform in a short timeframe with minimal burden to the operator, and (ii) quantified the level of random and systematic errors between sessions and systems, ensuring comparability of data in a variety of protocol setups, including repeated measures, longitudinal studies and multicentric studies. View Full-Text
Keywords: optoelectronic stereophotogrammetry; 3D motion capture; quality control; spot check; accuracy; systematic errors; gait; human movement optoelectronic stereophotogrammetry; 3D motion capture; quality control; spot check; accuracy; systematic errors; gait; human movement
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MDPI and ACS Style

Scott, K.; Bonci, T.; Alcock, L.; Buckley, E.; Hansen, C.; Gazit, E.; Schwickert, L.; Cereatti, A.; Mazzà, C.; on behalf of the Mobilise-D Consortium. A Quality Control Check to Ensure Comparability of Stereophotogrammetric Data between Sessions and Systems. Sensors 2021, 21, 8223. https://doi.org/10.3390/s21248223

AMA Style

Scott K, Bonci T, Alcock L, Buckley E, Hansen C, Gazit E, Schwickert L, Cereatti A, Mazzà C, on behalf of the Mobilise-D Consortium. A Quality Control Check to Ensure Comparability of Stereophotogrammetric Data between Sessions and Systems. Sensors. 2021; 21(24):8223. https://doi.org/10.3390/s21248223

Chicago/Turabian Style

Scott, Kirsty, Tecla Bonci, Lisa Alcock, Ellen Buckley, Clint Hansen, Eran Gazit, Lars Schwickert, Andrea Cereatti, Claudia Mazzà, and on behalf of the Mobilise-D Consortium. 2021. "A Quality Control Check to Ensure Comparability of Stereophotogrammetric Data between Sessions and Systems" Sensors 21, no. 24: 8223. https://doi.org/10.3390/s21248223

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