Effect of Camera Position on the Robustness of a 2D Markerless Motion Capture System for Assessing Shoulder Kinematics

Key Points

• This research aims to evaluate how camera position affects the effectiveness of a 2D markerless motion capture system for shoulder movement assessment.
• Training of deep neural network ResNet-50 and evaluation using DeepLabCut for shoulder kinematics analysis.
• Testing multiple camera positions to determine influence on motion capture accuracy.
• Significant variations in capture accuracy based on camera position observed (p<0.05).
• Optimal camera position identified, enhancing robustness of shoulder kinematics assessment.
• Training with ResNet-50 yielded improved prediction accuracy compared to previous methods.