Estimation of the Moving Joint Axis in the Knee Joint by Motion Analysis Data (original) (raw)
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Knee Surgery, Sports Traumatology, Arthroscopy, 2012
Purpose The transepicondylar axis (TEA) has been used as a flexion axis of the knee and a reference of the rotational alignment of the femoral component. However, no study has showed dynamic normal knee kinematics employing TEA as the evaluation parameter throughout the full range of motion in vivo. The purpose of this study was to analyze dynamic kinematics of the normal knee through the full range of motion via the 3-dimensional to 2-dimensional registration technique employing TEA as the evaluation parameter. Methods Dynamic motion of the right knee was analyzed in 20 healthy volunteers (10 female, 10 male; mean age 37.2 years). Knee motion was observed as subjects squatted from standing with knee fully extended to maximum flexion. The following parameters were determined: (1) Anteroposterior translations of the medial and lateral ends of the TEA; and (2) changes in the angle of the TEA on the tibial axial plane (rotation angle). Results The medial end of the TEA demonstrated anterior translation (3.6 ± 3.0 mm) from full extension to 30°fl exion and demonstrated posterior translation (18.1 ± 3.7 mm) after 30°, while the lateral end of the TEA demonstrated consistent posterior translation (31.1 ± 7.3 mm) throughout knee flexion. All subjects exhibited femoral external rotation (16.9 ± 6.2°) relative to the tibia throughout knee flexion. Conclusion Compared to previously used parameters, the TEA showed bicondylar posterior translation from early flexion phase. These results provide control data for dynamic kinematic analyses of pathologic knees in the future and will be useful in the design of total knee prostheses.
Identification of Methods for Estimating Knee Rotation Axis
The Quantified Motion Analysis (QMA) has become in recent years a clinical examination whose understanding and improvement are being developed. Based on a three-dimensional projection of the body segments, the QMA must define these segments and their means of union, the axes and centers of articular rotation. Two main techniques exist: predictive estimation techniques and functional techniques which use a calibration movement to estimate the axes and centers of rotation. These latter techniques, known as functional, seem to show superiority in terms of reproducibility of the estimate of the axis of rotation of the knee, but no consensus exists. The same applies to the calibration movements used.
Gait & posture, 2015
We recently developed a new method for three-dimensional evaluation of mechanical factors affecting knee joint in order to help identify factors that contribute to the progression of knee osteoarthritis (KOA). This study aimed to verify the clinical validity of our method by evaluating knee joint dynamics during gait. Subjects were 41 individuals (14 normal knees; 8 mild KOAs; 19 severe KOAs). The positions of skin markers attached to the body were captured during gait, and bi-planar X-ray images of the lower extremities were obtained in standing position. The positional relationship between the markers and femorotibial bones was determined from the X-ray images. Combining this relationship with gait capture allowed for the estimation of relative movement between femorotibial bones. We also calculated the point of intersection of loading axis of knee on the tibial proximal surface (LAK point) to analyze knee joint dynamics. Knee flexion range in subjects with severe KOA during gait ...
ANALYSIS OF SKELETAL MOTION KINEMATICS FOR A KNEE MOVEMENT CYCLE
analisedemarcha.com
This study estimated the skeletal motion for a knee motion cycle. The surface markers on the thigh and the shank showed the computed displacement during in vivo motion analysis. This error was minimized using optimization procedure. The displacement was generally greater on the thigh than the shank. The minimization of error produced by this procedure was more successful on the thigh than the shank. The purpose of this study was to require high value motion data. These results provide the basis to calculate the instantaneous knee axis of rotation in a follow up study
An analytical model of the knee for estimation of internal forces during exercise
Journal of Biomechanics, 1998
An analytical model of the knee joint was developed to estimate the forces at the knee during exercise. Muscle forces were estimated based upon electromyographic activities during exercise and during maximum voluntary isometric contraction (MVIC), physiological cross-sectional area (PCSA), muscle fiber length at contraction and the maximum force produced by an unit PCSA under MVIC. Tibiofemoral compressive force and cruciate ligaments' tension were determined by using resultant force and torque at the knee, muscle forces, and orientations and moment arms of the muscles and ligaments. An optimization program was used to minimize the errors caused by the estimation of the muscle forces. The model was used in a ten-subject study of open kinetic chain exercise (seated knee extension) and closed kinetic chain exercises (leg press and squat). Results calculated with this model were compared to those from a previous study which did not consider muscle length and optimization. Peak tibiofemoral compressive forces were 3134$1040 N during squat, 3155$755 N during leg press and 3285$1927 N during knee extension. Peak posterior cruciate ligament tensions were 1868$878 N during squat, 1866$383 N during leg press and 959$300 N for seated knee extension. No significant anterior cruciate ligament (ACL) tension was found during leg press and squat. Peak ACL tension was 142$257 N during seated knee extension. It is demonstrated that the current model provided better estimation of knee forces during exercises, by preventing significant overestimates of tibiofemoral compressive forces and cruciate ligament tensions.
RESEARCH ARTICLE Reconstructing the knee joint mechanism from kinematic data
The interpretation of joint kinematics data in terms of displacements is a product of the type of movement, the measurement technique, and the underlying model of the joint implemented in optimization procedures. Kinematic constraints reducing the number of degrees of freedom are expected to compensate for measurement errors and noise, thus, increasing the reproducibility of joint angles. One approach already successfully applied by several groups approximates the healthy human knee joint as a compound hinge joint with minimal varus/valgus rotation. Most of these optimizations involve an orthogonality constraint. This contribution compares the effect of a model with and without orthogonality constraint on the obtained joint rotation angles. For this purpose kinematic data is simulated without noise and with normally distributed noise of varying size. For small noise the unconstrained model provides more accurate results while for larger noise this is the case for the constrained model. This can be attributed to the shape of the objective function of the unconstrained model near its minimum.
Journal of Medical and Biological Engineering, 2017
Velocity analysis in a joint is a major area of interest in research involving the dynamics of joints and in diagnosing and monitoring the progression of some diseases such as osteoarthritis. In this study, we provide a general analytical method to determine three-dimensional linear and angular velocity of a joint. The formulations presented are explicit, having neither the limitations of numerical methods nor the necessity of simplifying the joint to a hinge or spherical (ball and socket) joint. In addition to conventional analysis of joint kinematics where only the position and orientation of the joint is considered, velocity analysis provides more information regarding the dynamics of the joint. The methodology presented is a systematic approach and can be used for various joints. As an example, a formulation to measure the velocity of the tibiofemoral component of a knee joint is presented, in terms of clinical rotations by using a joint coordinate system. The method is used to examine the in vivo velocity formulations in five ovine stifle (knee) joints by using joint kinematic data measured with an instrumented spatial linkage. The results demonstrate that the classical hinge model of the knee joint cannot predict the exact three-dimensional velocity of the knee joint through the gait cycle for all subjects.