Bilateral Frontal Plane Lower Limb Alignment from Markerles Motion Capture During Gait is Correlated Across Severity of Knee OA but not Post-TKA

Description

The presentation from ISTA 2024 held in Nashville discusses the use of markerless motion capture technology to measure kinematics in a clinically accessible way. The speaker Dr Elise Laende explains that this technology utilizes synchronized off-the-shelf video cameras and deep learning algorithms to analyze full-body motion by identifying anatomical landmarks. The validation studies indicate that the results obtained from markerless systems are comparable to traditional marker-based methods, specifically in orthopedic applications.



The research focuses on joint kinematics, particularly comparing left and right knee movements across patients with varying degrees of knee status, including asymptomatic patients and those with severe knee osteoarthritis. The study recruited over 600 knees from patients visiting an orthopedic clinic, capturing their kinematic data during a one-minute walk using Sony cameras. Principal component analysis was employed to extract key motion characteristics, particularly frontal plane alignment.



Results show that significant correlations exist between the knee movements of the left and right sides, especially in patients whose knees had not been replaced. However, when a joint replacement was performed, these correlations diminished. This finding suggests a patient-specific alignment pattern that may persist despite disease progression. Dr Laende emphasizes the implications of analyzing patients holistically, accounting for both sides during assessment and treatment, thus leading toward improved individualized medical care.



The presentation concludes with a call for potential collaborations and the importance of standardized data collection across multiple centers to enhance research quality and depth.

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