In vivokinematics of human wrist joints: Combination of medical imaging and three-dimensional electrogoniometry (original) (raw)
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Registration of 6-DOFs electrogoniometry and CT medical imaging for 3D joint modeling
Journal of Biomechanics, 2002
The paper describes a method in which two data-collecting systems, medical imaging and electrogoniometry, are combined to allow the accurate and simultaneous modeling of both the spatial kinematics and the morphological surface of a particular joint. The joint of interest (JOI) is attached to a Plexiglas jig that includes four metallic markers defining a local reference system (R GONIO ) for the kinematics data. Volumetric data of the JOI and the R GONIO markers are collected from medical imaging. The spatial location and orientation of the markers in the global reference system (R CT ) of the medical-imaging environment are obtained by applying object-recognition and classification methods on the image dataset. Segmentation and 3D isosurfacing of the JOI are performed to produce a 3D model including two anatomical objects-the proximal and distal JOI segments. After imaging, one end of a custom-made 3D electrogoniometer is attached to the distal segment of the JOI, and the other end is placed at the R GONIO origin; the JOI is displaced and the spatial kinematics data is recorded by the goniometer. After recording, data registration from R GONIO to R CT occurred prior to simulation. Data analysis was performed using both joint coordinate system (JCS) and instantaneous helical axis (IHA).
Constrained Registration of the Wrist Joint
IEEE Transactions on Medical Imaging, 2009
Comparing wrist shapes of different individuals requires alignment of these wrists into the same pose. Unconstrained registration of the carpal bones results in anatomically non-feasible wrists. In this paper we propose to constrain the registration using the shapes of adjacent bones, by keeping the width of the gap between adjacent bones constant.
Heart, 2000
The purpose of this study was to obtain quantitative information of the relative displacements and rotations of the carpal bones during movement of the wrist. Axial helical CT scans were made of the wrists of 11 volunteers. The wrists were imaged in the neutral position with a conventional CT technique, and in 15-20 other postures ͑flexion-extension, radial-ulnar deviation͒ with a low-dose technique. A segmentation of the carpal bones was obtained by applying a deformable surface model to the regular-dose scan. Next, each carpal bone, the radius, and ulna in this scan was registered with the corresponding bone in each low-dose scan using a three-dimensional matching technique. A detailed definition of the surfaces of the carpal bones was obtained from the regulardose scans. The low-dose scans provided sufficient information to obtain an accurate match of each carpal bone with its counterpart in the regular-dose scan. Accurate estimates of the relative positions and orientations of the carpal bones during flexion and deviation were obtained. This quantification will be especially useful when monitoring changes in kinematics before and after operative interventions, like mini-arthrodeses. This technique can also be applied in the quantification of the movement of other bones in the body ͑e.g., ankle and cortical spine͒.
High-speed, three-dimensional kinematic analysis of the normal wrist
The Journal of Hand Surgery, 1998
Carpal kinematics during a wrist flexion/extension motion using high-speed videodata acquisition was investigated. A cadaver forearm was stabilized, allowing unconstrained excursion of the wrist for passive range of motion (ROM). The extensor and flexor pairs of the wrist were looped together and a 1-1b weight was attached to each pair, simulating synergistic muscle tension. Capitate/radius and third metacarpal/radius angles were calculated to determine which measurement would be best for determining global wrist angle. The average difference in capitate/radius and third metacarpal/radius angles at each respective flexion/extension wrist angle for all wrists was 1.1 o _+ 1.6 ~ (the maximum difference was 4~ Hence, the capitate-third metacarpal joint can be considered rigid. Capitate/lunate motion as described by capitateradius Euler angles ranged from -16.9 to 23.5 with total capitate/lunate motion of 40.5 (35%) in the 114 ~ total global wrist ROM measured. Radius/lunate motion as described by lunateradius angle ranged from -8.2 to 48.4 with total radius/lunate motion of 56.5 (49%) in the 114 ~ total global wrist ROM measured. During global wrist motion, the radiolunate joint contributes more motion in flexion than the capitolunate joint and the capitolunate joint contributes more motion in extension than the radiolunate joint. The instantaneous screw axes (ISAs) were calculated for each third metacarpal position with respect to the radius. The average distance difference between ISAs for the 4 wrists tested was -1.23 + 14.97 pixels. The maximum distance was 56.51 pixels and the minimum was -24.09 pixels. This new combination of motion analysis and 3-dimensional reconstructions of computed tomography images affords a high-speed, dynamic analysis of kinematics. It shows that during wrist flexion/extension, normal carpal kinematics does not have an ISA fixed in or limited to the capitate. In addition, the ISA data provide evidence that translational motion is a real and measurable component of normal carpal motion. These findings alter the understanding of carpal kinematics obtained from the results of previous studies which suggested that the center of rotation was fixed in the capitate. (J Hand Surg 1998;23A:446-453.
Evaluation of a motion tracking model of the upper limb, including the hand
2017
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 (
Computed tomography based real-time joint kinematics during in-vitro tests
2017
INTRODUCTION To assess and compare the effect of new orthopedic surgical procedures, in vitro evaluation remains critical during the pre-clinical validation. Focusing on reconstruction surgery, the ability to restore normal kinematics and stability is thereby of primary importance. Therefore, several simulators have been developed to study the kinematics and create controlled boundary conditions [1,2]. To simultaneously capture the kinematics in six degrees of freedom as outlined by Grood & Suntay [3], markers are often rigidly connected to the moving bone segments. The position of these markers can subsequently be tracked while their position relative to the bones is determined using computed tomography (CT) of the test specimen with the markers attached [4]. Although this method serves as golden standard, it clearly lacks real-time feedback. Therefore, this paper presents the validation of a newly developed real-time framework to assess knee kinematics at the time of testing. Health
Journal of Biomechanics, 1998
This paper describes the design and performance evaluation of a three-dimensional (3-D) coordinate digitizing system (3-DCDS) for measuring both soft and hard biological tissue. The system incorporates a visible semiconducting laser beam and an X-½ positioning table to directly measure 3-D coordinates that define surface points. Experiments conducted to evaluate the performance of the system showed that it delivers an accuracy of 0.1 m in the Z-direction and 1.4 m in the X-½ plane, and an overall system root-meansquared error (RMSE) of 8 m on surfaces with slopes of less than 45°. This error is lower than that of previously reported measurement techniques. The 3-DCDS measures 3-D coordinates of surface points uniformly separated by 500 m in the X-½ plane. Because the 3-DCDS is automated, the coordinates are measured efficiently and the accuracy is independent of operator skill. These highly accurate coordinates can be easily incorporated into nodal values for 3-D finite element models (FEM) of diarthrodial joints. To show the use of the 3-DCDS, the 3-D surface coordinates of human menisci were measured from a cadaver specimen. 1998 Elsevier Science Ltd. All rights reserved.
3D Analysis of the Proximal Interphalangeal Joint Kinematics during Flexion
Computational and Mathematical Methods in Medicine, 2013
Background. Dynamic joint motion recording combined with CT-based 3D bone and joint surface data is accepted as a helpful and precise tool to analyse joint. The purpose of this study is to demonstrate the feasibility of these techniques for quantitative motion analysis of the interphalangeal joint in 3D.Materials and Method. High resolution motion data was combined with an accurate 3D model of a cadaveric index finger. Three light-emitting diodes (LEDs) were used to record dynamic data, and a CT scan of the finger was done for 3D joint surface geometry. The data allowed performing quantitative evaluations such as finite helical axis (FHA) analysis, coordinate system optimization, and measurement of the joint distances in 3D.Results. The FHA varies by4.9±1.7° on average. On average, the rotation in adduction/abduction and internal/external rotation were0.3±0.91° and0.1±0.97°, respectively. During flexion, a translational motion between 0.06 mm and 0.73 mm was observed.Conclusions. Th...
Journal of biomechanics, 2005
In this communication, the Standardization and Terminology Committee (STC) of the International Society of Biomechanics proposes a definition of a joint coordinate system (JCS) for the shoulder, elbow, wrist, and hand. For each joint, a standard for the local axis system in each articulating segment or bone is generated. These axes then standardize the JCS. The STC is publishing these recommendations so as to encourage their use, to stimulate feedback and discussion, and to facilitate further revisions. Adopting these standards will lead to better communication among researchers and clinicians. r