Markerless motion capture: What clinician-scientists need to know right now
| Author(s) | Ito, Naoaki | |
| Author(s) | Sigurðsson, Haraldur B. | |
| Author(s) | Seymore, Kayla D. | |
| Author(s) | Arhos, Elanna K. | |
| Author(s) | Buchanan, Thomas S. | |
| Author(s) | Snyder-Mackler, Lynn | |
| Author(s) | Grävare Silbernagel, Karin | |
| Date Accessioned | 2023-01-10T21:03:22Z | |
| Date Available | 2023-01-10T21:03:22Z | |
| Publication Date | 2022-11-14 | |
| Description | This article was originally published in Journal of Science and Medicine in Sport Plus. The version of record is available at: https://doi.org/10.1016/j.jsampl.2022.100001 | |
| Abstract | 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. | |
| Sponsor | National Institutes of Health R37-HD037985 provided tuition and stipend support for NI’s work. NIH R01-AR072034 provided stipend support for HBS and tuition and stipend support for KDS’s work. NIH F31-AR078580 and Foundation for Physical Therapy Research PODS II Scholarship provided tuition and stipend support for EKA's work. Theia Markerless provided the cameras and software necessary to use in this study. | |
| Citation | Ito, Naoaki, Haraldur B. Sigurðsson, Kayla D. Seymore, Elanna K. Arhos, Thomas S. Buchanan, Lynn Snyder-Mackler, and Karin Grävare Silbernagel. “Markerless Motion Capture: What Clinician-Scientists Need to Know Right Now.” JSAMS Plus 1 (2022): 100001. https://doi.org/10.1016/j.jsampl.2022.100001. | |
| ISSN | 2772-6967 | |
| URL | https://udspace.udel.edu/handle/19716/32044 | |
| Language | en_US | |
| Publisher | Journal of Science and Medicine in Sport Plus | |
| Keywords | Markerless motion capture | |
| Keywords | 3D modeling | |
| Keywords | lower extremity | |
| Keywords | kinematics | |
| Title | Markerless motion capture: What clinician-scientists need to know right now | |
| Type | Article |
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