Knee Joint Secondary Motion Accuracy Improved by Quaternion-Based Optimizer With Bony Landmark Constraints

2010 ◽  
Vol 132 (12) ◽  
Author(s):  
Hongsheng Wang ◽  
Naiqaun (Nigel) Zheng
Keyword(s):  
Soft Tissue ◽  
Knee Joint ◽  
Motion Analysis ◽  
Optimization Technique ◽  
Axial Rotation ◽  
Bony Landmark ◽  
Lateral Translation ◽  
Bony Landmarks ◽  
Tissue Movement ◽  
Rms Error

Skin marker-based motion analysis has been widely used in biomechanical studies and clinical applications. Unfortunately, the accuracy of knee joint secondary motions is largely limited by the nonrigidity nature of human body segments. Numerous studies have investigated the characteristics of soft tissue movement. Utilizing these characteristics, we may improve the accuracy of knee joint motion measurement. An optimizer was developed by incorporating the soft tissue movement patterns at special bony landmarks into constraint functions. Bony landmark constraints were assigned to the skin markers at femur epicondyles, tibial plateau edges, and tibial tuberosity in a motion analysis algorithm by limiting their allowed position space relative to the underlying bone. The rotation matrix was represented by quaternion, and the constrained optimization problem was solved by Fletcher’s version of the Levenberg–Marquardt optimization technique. The algorithm was validated by using motion data from both skin-based markers and bone-mounted markers attached to fresh cadavers. By comparing the results with the ground truth bone motion generated from the bone-mounted markers, the new algorithm had a significantly higher accuracy (root-mean-square (RMS) error: 0.7±0.1 deg in axial rotation and 0.4±0.1 deg in varus-valgus) in estimating the knee joint secondary rotations than algorithms without bony landmark constraints (RMS error: 1.7±0.4 deg in axial rotation and 0.7±0.1 deg in varus-valgus). Also, it predicts a more accurate medial-lateral translation (RMS error: 0.4±0.1 mm) than the conventional techniques (RMS error: 1.2±0.2 mm). The new algorithm, using bony landmark constrains, estimates more accurate secondary rotations and medial-lateral translation of the underlying bone.

Soft-Tissue Movement at the Foot During the Stance Phase of Walking

2011 ◽  
Vol 101 (1) ◽  
pp. 25-34 ◽  
Author(s):  
Shing-Jye Chen ◽  
Mukherjee Mukul ◽  
Li-Shan Chou
Keyword(s):  
Young Adults ◽  
Soft Tissue ◽  
Lower Limb ◽  
Stance Phase ◽  
Lower Limb Injury ◽  
Limb Injury ◽  
Motion System ◽  
Bony Landmarks ◽  
Tissue Movement ◽  
Intermarker Distance

Background: Soft-tissue movement has challenged the use of noninvasive skin-based markers that are assumed to be rigidly attached to the underlying bony landmarks. We assessed soft-tissue movement in multiple foot segments by calculating the relative changes in the intermarker distances of the hindfoot, midfoot, and forefoot segments during the early, middle, and late stances of walking compared with the intermarker distances measured while participants remained still during standing. Methods: Seven healthy young adults with no previous lower-limb injury were tested while walking barefoot at a comfortable pace. Skin-based markers were placed on three foot regions (hindfoot-calcaneus, midfoot-navicular, and forefoot–first to fifth metatarsals). A motion system sampled at 120 Hz was used to capture the foot markers during the stance phase of walking. Results: Soft-tissue movement was found in the forefoot region characterized by shortened distances, specifically during early (breaking) stance and late (propulsion) stance. In the hindfoot region, soft-tissue movement was characterized by shortened and elongated distances during the early and late stance periods, respectively. All of the foot regions showed the least intermarker distance changes during midstance. Conclusions: The dynamics of soft-tissue movement in multiple foot segments were characterized by the greatest changes in the intermarker distances in the forefoot and hindfoot during the early and late stance phases and the least changes in the foot segments during midstance. The results provide a feasible and accessible measurement for assessing soft-tissue movement in the foot when skin-based motion markers are used. (J Am Podiatr Med Assoc 101(1): 25–34, 2011)

scholarly journals The Influence of Kinematic Constraints on Model Performance During Inverse Kinematics Analysis of the Thoracolumbar Spine

2021 ◽  
Vol 9 ◽  
Author(s):  
Mohammad Mehdi Alemi ◽  
Katelyn A. Burkhart ◽  
Andrew C. Lynch ◽  
Brett T. Allaire ◽  
Seyed Javad Mousavi ◽  
...  
Keyword(s):  
Motion Analysis ◽  
Inverse Kinematics ◽  
Intraclass Correlation ◽  
Axial Rotation ◽  
Kinematics Analysis ◽  
Lateral Bending ◽  
Kinematic Constraints ◽  
Flexion Extension ◽  
Spine Motion ◽  
Rms Error

Motion analysis is increasingly applied to spine musculoskeletal models using kinematic constraints to estimate individual intervertebral joint movements, which cannot be directly measured from the skin surface markers. Traditionally, kinematic constraints have allowed a single spinal degree of freedom (DOF) in each direction, and there has been little examination of how different kinematic constraints affect evaluations of spine motion. Thus, the objective of this study was to evaluate the performance of different kinematic constraints for inverse kinematics analysis. We collected motion analysis marker data in seven healthy participants (4F, 3M, aged 27–67) during flexion–extension, lateral bending, and axial rotation tasks. Inverse kinematics analyses were performed on subject-specific models with 17 thoracolumbar joints allowing 51 rotational DOF (51DOF) and corresponding models including seven sets of kinematic constraints that limited spine motion from 3 to 9DOF. Outcomes included: (1) root mean square (RMS) error of spine markers (measured vs. model); (2) lag-one autocorrelation coefficients to assess smoothness of angular motions; (3) maximum range of motion (ROM) of intervertebral joints in three directions of motion (FE, LB, AR) to assess whether they are physiologically reasonable; and (4) segmental spine angles in static ROM trials. We found that RMS error of spine markers was higher with constraints than without (p < 0.0001) but did not notably improve kinematic constraints above 6DOF. Compared to segmental angles calculated directly from spine markers, models with kinematic constraints had moderate to good intraclass correlation coefficients (ICCs) for flexion–extension and lateral bending, though weak to moderate ICCs for axial rotation. Adding more DOF to kinematic constraints did not improve performance in matching segmental angles. Kinematic constraints with 4–6DOF produced similar levels of smoothness across all tasks and generally improved smoothness compared to 9DOF or unconstrained (51DOF) models. Our results also revealed that the maximum joint ROMs predicted using 4–6DOF constraints were largely within physiologically acceptable ranges throughout the spine and in all directions of motions. We conclude that a kinematic constraint with 5DOF can produce smooth spine motions with physiologically reasonable joint ROMs and relatively low marker error.

scholarly journals Association Between Pain in Knee Osteoarthritis and Mechanical Properties of Soft Tissue Around Knee Joint

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 14599-14607
Author(s):  
Jianan Wu ◽  
Zhihui Qian ◽  
Ruixia Xu ◽  
Jing Liu ◽  
Luquan Ren ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Soft Tissue ◽  
Knee Joint ◽  
Knee Osteoarthritis

scholarly journals An Investigation into a Gear-Based Knee Joint Designed for Lower Limb Prosthesis

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
M. S. H. Bhuiyan ◽  
I. A. Choudhury ◽  
M. Dahari ◽  
Y. Nukman ◽  
S. Z. Dawal
Keyword(s):  
Knee Joint ◽  
Motion Analysis ◽  
Maximum Stress ◽  
Real Data ◽  
Fe Analysis ◽  
Knee Prostheses ◽  
Maximum Displacement ◽  
Element Analysis ◽  
Lower Limb Prosthesis ◽  
Limb Prosthesis

A gear-based knee joint is designed to improve the performance of mechanical-type above-knee prostheses. The gear set with the help of some bracing, and bracket arrangement, is used to enable the prosthesis to follow the residual limb movement. The motion analysis and finite-element analysis (FEA) of knee joint components are carried out to assess the feasibility of the design. The maximum stress of 29.74 MPa and maximum strain of 2.393e−004 are obtained in the gear, whereas the maximum displacement of 7.975 mm occurred in the stopper of the knee arrangement. The factor of safety of 3.5 obtained from the FE analysis indicated no possibility of design failure. The results obtained from the FE analysis are then compared with the real data obtained from the literature for a similar subject. The pattern of motion analysis results has shown a great resemblance with the gait cycle of a healthy biological limb.

BIOMECHANICAL ANALYSIS OF THE STANDING LONG JUMP

2003 ◽  
Vol 15 (05) ◽  
pp. 186-192 ◽  
Author(s):  
WEN-LAN WU ◽  
JIA-HROUNG WU ◽  
HWAI-TING LIN ◽  
GWO-JAW WANG
Keyword(s):  
Knee Joint ◽  
Motion Analysis ◽  
Joint Angle ◽  
Three Dimensional ◽  
The Body ◽  
Initial Angle ◽  
Knee Joint Angle ◽  
Standing Long Jump ◽  
Long Jump ◽  
Arm Motion

The purposes of the present study were to (1) investigate the effects of the arm movement and initial knee joint angle employed in standing long jump by the ground reaction force analysis and three-dimensional motion analysis; and (2) investigate how the jump performance of the female gender related to the body configuration. Thirty-four healthy adult females performed standing long jump on a force platform with full effort. Body segment and joint angles were analyzed by three-dimensional motion analysis system. Using kinetic and kinematic data, the trajectories on mass center of body, knee joint angle, magnitude of peak takeoff force, and impulse generation in preparing phase were calculated. Average standing long jump performances with free arm motion were +1.5 times above performance with restricted arm motion in both knee initial angles. The performances with knee 90° initial flexion were +1.2 times above performance with knee 45° initial flexion in free and restricted arm motions. Judging by trajectories of the center mass of body (COM), free arm motion improves jump distance by anterior displacement of the COM in starting position. The takeoff velocity with 90° knee initial angle was as much as 11% higher than in with 45° knee initial angle. However, the takeoff angles on the COM trajectory showed no significant differences between each other. It was found that starting jump from 90° bend knee relatively extended the time that the force is applied by the leg muscles. To compare the body configurations and the jumping scores, there were no significant correlations between jump scores and anthropometry data. The greater muscle mass or longer leg did not correlated well with the superior jumping performance.

The Effects of Tibiofemoral Angle and Body Weight on the Stress Field in the Knee Joint

2007 ◽  
Author(s):  
Nicholas H. Yang ◽  
H. Nayeb-Hashemi ◽  
Paul K. Canavan
Keyword(s):  
Articular Cartilage ◽  
Knee Joint ◽  
Motion Analysis ◽  
Stance Phase ◽  
Gait Cycle ◽  
Mechanical Axis ◽  
Frontal Plane ◽  
Tibiofemoral Angle ◽  
Single Leg Stance ◽  
Von Mises

Osteoarthritis (OA) is a degenerative disease of articular cartilage that may lead to pain, limited mobility and joint deformation. It has been reported that abnormal stresses and irregular stress distribution may lead to the initiation and progression of OA. Body weight and the frontal plane tibiofemoral angle are two biomechanical factors which could lead to abnormal stresses and irregular stress distribution at the knee. The tibiofemoral angle is defined as the angle made by the intersection of the mechanical axis of the tibia with the mechanical axis of the femur in the frontal plane. In this study, reflective markers were placed on the subjects’ lower extremity bony landmarks and tracked using motion analysis. Motion analysis data and force platform data were collected together during single-leg stance, double-leg stance and walking gait from three healthy subjects with no history of osteoarthritis (OA), one with normal tibiofemoral angle (7.67°), one with varus (bow-legged) angle (0.20°) and one with valgus (knocked-knee) angle (10.34°). The resultant moment and forces in the knee were derived from the data of the motion analysis and force platform experiments using inverse dynamics. The results showed that Subject 1 (0.20° valgus) had a varus moment of 0.38 N-m/kg, during single-leg stance, a varus moment of 0.036 N-m/kg during static double-leg stance and a maximum varus moment of 0.49 N-m/kg during the stance phase of the gait cycle. Subject 2 (7.67° valgus tibiofemoral angle) had a varus moment of 0.31 N-m/kg, during single-leg stance, a valgus moment of 0.046 N-m/kg during static double-leg stance and a maximum varus moment of 0.37 N-m/kg during the stance phase of the gait cycle. Subject 3 (10.34° valgus tibiofemoral angle) had a varus moment of 0.30 N-m/kg, during single-leg stance, a valgus moment of 0.040 N-m/kg during static double-leg stance and a maximum varus moment of 0.34 N-m/kg during the stance phase of the gait cycle. In general, the results show that the varus moment at the knee joint increased with varus knee alignment in static single-leg stance and gait. The results of the motion analysis were used to obtain the knee joint contact stress by finite element analysis (FEA). Three-dimensional (3-D) knee models were constructed with sagittal view MRI of the knee. The knee model included the bony geometry of the knee, the femoral and tibial articular cartilage, the lateral and medial menisci and the cruciate and the collateral ligaments. In initial FEA simulations, bones were modeled as rigid, articular cartilage was modeled as isotropic elastic, menisci were modeled as transversely isotopic elastic, and the ligaments were modeled as 1-D nonlinear springs. The material properties of the different knee components were taken from previously published literature of validated FEA models. The results showed that applying the axial load and varus moment determined from the motion analysis to the FEA model Subject 1 had a Von Mises stress of 1.71 MPa at the tibial cartilage while Subjects 2 and 3 both had Von Mises stresses of approximately 1.191 MPa. The results show that individuals with varus alignment at the knee will be exposed to greater stress at the medial compartment of the articular cartilage of the tibia due to the increased varus moment that occurs during single leg support.

scholarly journals Motion analysis for the mobile bearing tka using the knee joint simulator with a parallel link 6-dof actuator

2004 ◽  
Vol 28 (2) ◽  
pp. 84-90 ◽  
Author(s):  
Hidehiko HIGAKI ◽  
Koji KUMAMOTO ◽  
Takeshi SHIMOTO ◽  
Takatosi UMENO ◽  
Yoshitaka NAKANISHI ◽  
...  
Keyword(s):  
Knee Joint ◽  
Motion Analysis ◽  
Mobile Bearing ◽  
Parallel Link

scholarly journals Synovial sarcoma presenting as subcutaneous swelling: a rare presentation

2019 ◽  
Vol 6 (6) ◽  
pp. 2190
Author(s):  
Dheer S. Kalwaniya ◽  
Jaspreet S. Bajwa
Keyword(s):  
Soft Tissue ◽  
Early Diagnosis ◽  
Knee Joint ◽  
Synovial Sarcoma ◽  
Lower Risk ◽  
Soft Tissue Sarcomas ◽  
Synovial Cells ◽  
Rare Presentation

Synovial sarcoma unlike its name is not originating from synovial cells. It accounts for approximately 10% of all soft tissue sarcomas with main predilection for extremities.We present here a case of synovial sarcoma of subcutaneous origin of knee joint which is rarest of presentations and early diagnosis is associated with lower risk of metastasis and hence better prognosis.

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