2 research outputs found

    Biomechanical role and motion contribution of ligaments and bony constraints in the elbow stability: A preliminary study

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    In flexion-extension motion, the interaction of several ligaments and bones characterizes the elbow joint stability. The aim of this preliminary study was to quantify the relative motion of ulna respect to humerus in two human elbow specimens and to investigate the constraints role for maintaining the joint stability in different dissections condition. Two clusters of 4 markers were fixed respectively to ulna and humerus, and their trajectory was recorded by a motion capture system during orthopedic maneuver. Considering the medial ulnar collateral posterior bundle (pMUCL) and the coronoid, two dissection sequences were executed. The orthopedic maneuver of compression, pronation and varus force was repeated at 30°, 60°, 90° flexion for the functional investigation of constraints. Ulna deflection was compared to a baseline flexion condition. Respect to intact elbow, the coronoid osteotomy influences the elbow stability at 90° (deflection=11.49±17.39 mm), while small differences occur at 30° and 60°, due to ligaments constraint. The contemporary pMUCL dissection and coronoid osteotomy causes elbow instability, with large deflection at 30° (deflection=34.40±9.10 mm), 60° (deflection=45.41±18.47 mm) and 90° (deflection=52.16±21.92 mm). Surgeons may consider the pMUCL reconstruction in case of unfixable coronoid fracture

    Estimation of joint position error

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    Joint position error (JPE) is frequently used to assess proprioception in rehabilitation and sport science. During position-reposition tests the subject is asked to replicate a specific target angle (e.g. 30° of knee flexion) for a specific number of times. The aim of this study is to find an effective method to estimate JPE from the joint kinematic signal. Forty healthy subjects were tested to assess knee joint position sense. Three different methods of JPE estimation are described and compared using a hierarchical clustering approach. Overall, the 3 methods showed a high degree of similarity, ranging from 88% to 100%. We concluded that it is preferable to use the more user-independent method, in which the operator does not have to manually place "critical" markers
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