[Lower limb joint contact forces and ground reaction forces analysis based on Azure Kinect motion capture]

Area of Science:

• Biomechanics
• Motion Analysis
• Computational Modeling

Context:

• Traditional gait analysis systems are expensive, cumbersome, and lack portability.
• There is a need for accessible and efficient motion capture technologies in biomechanics research.
• Azure Kinect offers a potential solution for real-time, low-cost motion capture.

Purpose:

• To develop and validate a musculoskeletal dynamics calculation process using Azure Kinect skeletal data.
• To assess the accuracy of Azure Kinect-based lower limb joint angles, joint contact forces, and ground reaction forces.
• To compare the performance of the Azure Kinect model against the gold-standard Vicon system.

Summary:

• A musculoskeletal model was developed using Azure Kinect skeletal data from 10 participants.
• The model computed lower limb joint angles, joint contact forces, and ground reaction forces.
• Results were validated against data from a traditional Vicon system, showing strong correlations for forces but notable errors in joint angles.

Impact:

• The Azure Kinect-based model demonstrates good predictive capabilities for lower limb joint forces and vertical ground reaction forces.
• This approach offers a more accessible and portable method for musculoskeletal dynamics analysis.
• Further improvements are needed to enhance the accuracy of lower limb joint angle predictions.