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Related Concept Videos

Functional Classification of Joints01:09

Functional Classification of Joints

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Functional Classification of Joints
The functional classification of joints is determined by the amount of mobility between the adjacent bones. Joints are functionally classified as a synarthrosis or immobile joint, an amphiarthrosis or slightly moveable joint, or as a diarthrosis, a freely moveable joint. Fibrous and cartilaginous joints can be functionally classified as either synarthroses  or amphiarthroses, whereas all synovial joints are classified as diarthroses.
Synarthrosis
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Knee Joint01:23

Knee Joint

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The knee joint is the most complicated joint in the body. It consists of three articulations– two tibiofemoral and one patellofemoral. As is characteristic of synovial joints, the knee joint has a thin articular capsule that partially surrounds this joint cavity. Additionally, several ligaments, muscles, and cartilaginous structures support the movement of the knee.
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Structural Classification of Joints01:20

Structural Classification of Joints

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Joints, also known as articulations, are classified based on their structural characteristics, i.e., based on whether the articulating surfaces of the adjacent bones are directly connected by fibrous connective tissue or cartilage, or whether the articulating surfaces contact each other within a fluid-filled joint cavity. These differences serve to divide the joints of the body into three structural classifications.
A fibrous joint is where the adjacent bones are united by fibrous connective...
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Updated: May 31, 2025

In Vivo Quantification of Hip Arthrokinematics during Dynamic Weight-bearing Activities using Dual Fluoroscopy
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Benefits of Using Functional Joint Coordinate Systems in In Vitro Knee Testing.

Tara F Nagle1, Jeremy G Loss1, Robb W Colbrunn1

  • 1Department of Biomedical Engineering and Lerner Research Institute, Cleveland Clinic, 2111 E. 96th Street, Cleveland, OH 44106.

Journal of Biomechanical Engineering
|January 22, 2025
PubMed
Summary
This summary is machine-generated.

Using functional coordinate systems (CS) in knee joint biomechanics testing significantly reduces kinematic variation and improves force control. This study demonstrates the benefits of functional CS over anatomical CS for more accurate in vitro knee joint analysis.

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Area of Science:

  • Biomechanics
  • Orthopedics
  • Musculoskeletal Research

Background:

  • Accurate measurement of knee joint kinematics requires defining coordinate systems (CS) for the tibia and femur.
  • Functional CS have demonstrated higher reproducibility compared to anatomical CS in previous studies.

Purpose of the Study:

  • To quantify the advantages of employing functional CS over anatomical CS in in vitro knee joint testing.
  • To assess the impact of CS definition on kinematic response variation, cross-talk, and force control.

Main Methods:

  • Seven cadaveric knee joints were subjected to six-degree-of-freedom (DOF) loading in a specialized joint simulator.
  • Both anatomical and functional CS were established for each knee joint.
  • Loading profiles were applied, and kinematics and kinetics were recorded to compare the two CS definitions.

Main Results:

  • Functional CS significantly reduced intra-knee kinematic response variation across various loading conditions.
  • Kinematic cross-talk was significantly reduced during laxity testing (anterior-posterior, varus-valgus, internal-external rotation) with functional CS.
  • Inter-knee kinematic response variation was significantly lower for all DOFs using functional CS during gait and combined loading.
  • Force/torque control performance for anterior-posterior and varus-valgus loading was significantly improved with functional CS.

Conclusions:

  • Functional CS offer significant advantages over anatomical CS for in vitro knee joint testing.
  • The use of functional CS leads to more accurate and reproducible kinematic measurements and improved force control.
  • It is recommended to utilize functional CS for all in vitro knee joint studies to enhance data reliability.