Markerless motion capture: What clinician-scientists need to know right now

• Main Authors: Naoaki Ito (Author), Haraldur B. Sigurðsson (Author), Kayla D. Seymore (Author), Elanna K. Arhos (Author), Thomas S. Buchanan (Author), Lynn Snyder-Mackler (Author), Karin Grävare Silbernagel (Author)
• Format: Book
• Published: Elsevier, 2022-10-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 2772-6967; 10.1016/j.jsampl.2022.100001
• Keywords: Markerless motion capture; 3D modeling; Lower extremity; Kinematics; Sports; GV557-1198.995; Sports medicine; RC1200-1245
• Source: JSAMS Plus, Vol 1, Iss , Pp 100001- (2022)

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.