Using musculoskeletal modelling to estimate knee joint loading pre and post high tibial osteotomy

Bowd, Jake; Rossom, Sam Van; Williams, David; Elson, David W.; Wilson, Chris; Whatling, Gemma Marie; Holt, Cathy; Jonkers, Ilse

doi:10.1016/j.clinbiomech.2022.105855

Cited by 3 publications

(2 citation statements)

References 20 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Motion estimation is a challenge in the field of computer vision. In the literature, the instant compression of 3D point cloud sequences has been ignored, and there are many existing articles to compress static 3-D point clouds [3][4][5][6][7][8][9][10][11][12][13][14][15][16]. The literature study comprises techniques that start with graphical compression representations and deep learning frameworks for 3D point cloud sequences with view-based literature.…”

Section: Review Workmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Detection of Tibiofemoral Joint Kinematical Space using Graph-based Model of 3D Point Cloud Sequences

Pattanaik

Alsubaie

Alqahtani

et al. 2023

Preprint

View full text Add to dashboard Cite

The goal of this paper is to tackle the challenge of estimating motion in sequences of 3D point clouds that feature the movement of the knee joint's 3D positions and color attributes. Kinematics and morphology (form) are two important factors in determining the features of flexion and extension. Joints are crucial parts of the linear motion system. Precise estimation of both moments and shape is required to comprehend the functionality of joint surfaces (e.g., the knee). The diagnosis of knee pathologies and treatment of chronic joint diseases such as Osteoarthritis requires an accurate understanding of the in vivo biomechanics of the human knee. However, measuring kinematics in human patients is challenging. The dynamic monitoring of knee motions, whereby generates a realistic bone model that includes and excludes cartilage, can be used to create a novel measurement technique for knee investigations. Such morph kinematic modeling offers the chance to analyze the knee's kinematics and examine interrelations like surfaces in contact or regions. Our purpose is to apply a 3D cloud point database and rigid femur and tibial skeleton to determine motion from the morphology of knee joints. As far as we are aware, this new research paper is the first to utilize both the spatial correlation within each frame (represented by a graph) and the temporal correlation between frames (represented by motion estimation) to enhance the accuracy of joint shape and movement analysis in the context of osteoarthritis. The 3D factor cloud order is in better shape. With the help of a 3D statistical knee database from morphology, our paper proposes a technique for quantifying knee kinematics (motion) (shape).

show abstract

Section: Review Workmentioning

confidence: 99%

“…The most commonly used techniques are radiography and magnetic resonance imaging (MRI) [4]. OA causes changes in ligaments, muscles, synovium, subchondral bone, articular cartilage, and subchondral bone.…”

Section: Introductionmentioning

confidence: 99%

A Novel Detection of Tibiofemoral Joint Kinematical Space using Graph-based Model of 3D Point Cloud Sequences

Pattanaik

Alsubaie

Alqahtani

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

Around-the-knee osteotomies part 1: definitions, rationale and planning—state of the art

Kayaalp,

Apseloff,

Lott

et al. 2024

Journal of ISAKOS

View full text Add to dashboard Cite

Quadriceps Muscle and Medial Retinaculum Combinate Effects on Patellar Instability during Knee Flexion

2023

View full text Add to dashboard Cite

Background: Patellar instability can cause pain and disability. A finite element model of a healthy human knee was performed to analyze the role of quadriceps and medial retinaculum imbalance in patellar instability. Methods: The model was created by matching magnetic resonance and computed tomography images of a normal adult patient’s knee. Muscle force intensities were calculated by static optimization, considering the lower limb muscles, knee movement and the ground reaction during walking. Patellar instability was experimentally generated by progressively uncoupling muscular forces, (90 N versus 110 N), while at the same time, the load derived from the quadriceps was gradually reduced by 20%. Results: This loss in force symmetry of 10 N on the retinaculum may produce a displacement of approximately 7 mm, with an increase in patellar contact forces of approximately 44%. When the quadriceps force is reduced by 10% and the unbalanced medial retinaculum acts together, the displacements are in the order of 14 mm, and the patellar contact forces increase by 84%. Conclusion: A reduced quadriceps force alone is not able to cause significant patellar instability, while an imbalance of forces at the level of the retinaculum could lead to patellar instability, especially when the two effects are combined. A better understanding of joint relationships and muscle synergies can help to improve clinical approaches to patella instability

show abstract

Using musculoskeletal modelling to estimate knee joint loading pre and post high tibial osteotomy

Cited by 3 publications

References 20 publications

A Novel Detection of Tibiofemoral Joint Kinematical Space using Graph-based Model of 3D Point Cloud Sequences

A Novel Detection of Tibiofemoral Joint Kinematical Space using Graph-based Model of 3D Point Cloud Sequences

Around-the-knee osteotomies part 1: definitions, rationale and planning—state of the art

Quadriceps Muscle and Medial Retinaculum Combinate Effects on Patellar Instability during Knee Flexion

Contact Info

Product

Resources

About