Markerless motion capture: What clinician-scientists need to know right now
Naoaki Ito,
Haraldur B. Sigurðsson,
Kayla D. Seymore,
Elanna K. Arhos,
Thomas S. Buchanan,
Lynn Snyder-Mackler,
Karin Grävare Silbernagel
Affiliations
Naoaki Ito
Biomechanics and Movement Science Program, University of Delaware, Newark, DE, USA; Department of Physical Therapy, University of Delaware, Newark, DE, USA
Haraldur B. Sigurðsson
Biomechanics and Movement Science Program, University of Delaware, Newark, DE, USA; Department of Physical Therapy, University of Delaware, Newark, DE, USA; Department of Physical Therapy, University of Iceland, Reykjavik, Iceland
Kayla D. Seymore
Biomechanics and Movement Science Program, University of Delaware, Newark, DE, USA; Department of Physical Therapy, University of Delaware, Newark, DE, USA
Elanna K. Arhos
Biomechanics and Movement Science Program, University of Delaware, Newark, DE, USA; Department of Physical Therapy, University of Delaware, Newark, DE, USA
Thomas S. Buchanan
Biomechanics and Movement Science Program, University of Delaware, Newark, DE, USA; Department of Biomedical Engineering, University of Delaware, Newark, DE, USA; Mechanical Engineering, University of Delaware, Newark, DE, USA
Lynn Snyder-Mackler
Biomechanics and Movement Science Program, University of Delaware, Newark, DE, USA; Department of Physical Therapy, University of Delaware, Newark, DE, USA; Mechanical Engineering, University of Delaware, Newark, DE, USA
Karin Grävare Silbernagel
Biomechanics and Movement Science Program, University of Delaware, Newark, DE, USA; Department of Physical Therapy, University of Delaware, Newark, DE, USA; Department of Biomedical Engineering, University of Delaware, Newark, DE, USA; Corresponding author. 540 S. College Ave, Newark, DE 19713, USA. Fax: +302 269-8011.
Markerless motion capture (mocap) could be the future of motion analysis. The purpose of this report was to describe our team of clinicians and scientists’ exploration of markerless mocap (Theia 3D) and share data for others to explore (link: https://osf.io/6vh7z/?view_only=c0e00984e94a48f28c8d987a2127339d). Simultaneous mocap was performed using markerless and marker-based systems for walking, squatting, and forward hopping. Segment lengths were more variable between trials using markerless mocap compared to marker-based mocap. Sagittal plane angles were most comparable between systems at the knee joint followed by the ankle and hip. Frontal and transverse plane angles were not comparable between systems. The data collection experience using markerless mocap was simpler, faster, and user friendly. The ease of collection was in part offset by the added data transfer and processing times, and the lack of troubleshooting flexibility. If used selectively with proper understanding of limitations, markerless mocap can be exciting technology to advance the field of motion analysis.
