Kinematics Analysis of the Elbow Joint; Comparison of the Kinematics of the Left and Right Elbow (original) (raw)
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Journal of biomechanics, 2005
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Evaluation of a motion tracking model of the upper limb, including the hand
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The characterization of human motion is an important field in Biomechanics. The recording of the movement by using videogrammetric techniques has the advantage of not interfering with the normal development of the human movement. In the upper limb, it can be used to assess the impact of different pathologies on functionality or to improve the design of upper limb prostheses according to patients' needs, among others. Videogrammetric systems are in widespread use amongst biomechanical researchers worldwide. They allow obtaining the 3D positions of a set of markers attached to the body. Commercial systems, such as Vicon®, include models for the analysis of the upper-limb motion, not including the detailed motion of the hand. Models for the study of the hand movement are scarce or poorly described. Sancho-Bru et al. (2014) presented a detailed model, hereby referred to as UJI-Hand model, allowing the measurement of 25 anatomical angles. In this work, the adaptation of the UJI-Hand model to the existent Vicon® Upper-Limb model is presented, in order to obtain the anatomical angles of the full upper limb, including the hand. Depending on the researcher needs to minimize the effects of occlusion amongst markers, removal of two adhesive markers has been set as an option, at carpometacarpal joints of the middle and ring fingers. These markers are interpolated from the location of the remaining ones. The maximum difference introduced in the observation by this simplification, evaluated on 10 subjects, has been established in 1.8º at the metacarpophalangeal joint of the middle finger. The total average for the affected joints was 1.08º. The procedure of post-processing the 3D position of the markers to obtain the joint angles has been fully documented and implemented in Matlab® using homogenous transformation matrices. The code is available to the scientific community as UJI-Hand Toolbox (
A Physiological Dynamic Testing Machine for the Elbow Joint
Background: The aim of our study was to develop a test setup combining realistic force transmission with physiological movement patterns at a frequency that mimicked daily use of the elbow, to assess implants in orthopedic joint reconstruction and trauma surgery. Methods: In a multidisciplinary approach, an in vitro biomechanical testing machine was developed and manufactured that could simulate the repetitive forceful movement of the human elbow joint. The construction involved pneumatic actuators. An aluminum forearm module enabled movements in 3 degrees of freedom, while motions and forces were replicated via force and angular sensors that were similar to in vivo measurements. Results: In the initial testing, 16 human elbow joint specimens were tested at 35 Nm in up to 5000 cycles at a range of 10° extension to 110° flexion. The transmitted forces led to failure in 9 out of the 16 tested specimens, significantly more often in females and small specimens. Conclusions: It is possible to construct a testing machine to simulate nearly physiological repetitive elbow motions. The prototype has a number of technical deficiencies that could be modified. When testing implants for the human elbow with cadaver specimens, the specimen has to be chosen according to the intended use of the implant under investigation.
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Clinical Biomechanics, 2003
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A method for in-vivo kinematic analysis of the forearm
Journal of Biomechanics, 2008
Purpose: To develop a method for in-vivo kinematic study of normal forearm rotation using computed tomographic (CT) images and a custom apparatus which allows for control of amount of forearm rotation. Methods: The forearm of one asymptomatic volunteer was CT-scanned in five positions: neutral, 601 pronation, maximal pronation, 601 supination, and maximal supination. Surface registration of the pronated/supinated image datasets with the neutral position was performed. The resulting transformation matrices were decomposed into finite helical axis (FHA) parameters. Kinematics were expressed as motion of the radius relative to the ulna. Results: The axes of the forearm passed through the volar region of the radial head at the proximal radioulnar joint (PRUJ), extending towards the dorsal region of the ulnar head at the distal radioulnar joint (DRUJ). Distinct FHAs were calculated for each forearm position analyzed relative to neutral rotation. Forearm pronation FHAs were different from forearm supination FHAs. Conclusions: Our experimental methodology is capable of describing the in-vivo kinematics of the forearm with good accuracy and reliability. Future in-vivo studies would need to be performed using a larger sample size to further validate our preliminary results. An ideal clinical application of this methodology would be in the comparative study of patients with forearm dysfunction. r