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Comparison of Marker-Based and Stereo Radiography Knee Kinematics in Activities of Daily Living
Author(s) -
Donald R. Hume,
Vasiliki Kefala,
Michael D. Harris,
Kevin B. Shelburne
Publication year - 2018
Publication title -
annals of biomedical engineering
Language(s) - English
Resource type - Journals
eISSN - 1573-9686
pISSN - 0090-6964
DOI - 10.1007/s10439-018-2068-9
Subject(s) - kinematics , knee joint , valgus , biomechanics , motion capture , radiography , femur , orthodontics , medicine , mathematics , computer science , anatomy , artificial intelligence , motion (physics) , physics , radiology , surgery , classical mechanics
Movement of the marker positions relative to the body segments obscures in vivo joint level motion. Alternatively, tracking bones from radiography images can provide precise motion of the bones at the knee but is impracticable for measurement of body segment motion. Consequently, researchers have combined marker-based knee flexion with kinematic splines to approximate the translations and rotations of the tibia relative to the femur. Yet, the accuracy of predicting six degree-of-freedom joint kinematics using kinematic splines has not been evaluated. The objectives of this study were to (1) compare knee kinematics measured with a marker-based motion capture system to kinematics acquired with high speed stereo radiography (HSSR) and describe the accuracy of marker-based motion to improve interpretation of results from these methods, and (2) use HSSR to define and evaluate a new set of knee joint kinematic splines based on the in vivo kinematics of a knee extension activity. Simultaneous measurements were recorded from eight healthy subjects using HSSR and marker-based motion capture. The marker positions were applied to three models of the lower extremity to calculate tibiofemoral kinematics and compared to kinematics acquired with HSSR. As demonstrated by normalized RMSE above 1.0, varus-valgus rotation (1.26), medial-lateral (1.26), anterior-posterior (2.03), and superior-inferior translations (4.39) were not accurately measured. Using kinematic splines improved predictions in varus-valgus (0.81) rotation, and medial-lateral (0.73), anterior-posterior (0.69), and superior-inferior (0.49) translations. Using splines to predict tibiofemoral kinematics as a function knee flexion can lead to improved accuracy over marker-based motion capture alone, however this technique was limited in reproducing subject-specific kinematics.

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