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Related Experiment Video

Updated: Nov 26, 2025

Lower Limb Biomechanical Analysis of Healthy Participants
06:36

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Focusing on functional knee parameter determination to develop a better clinical gait analysis protocol.

J Leboucher1, F Salami1, O Öztürk2

  • 1Clinic for Orthopedics and Trauma Surgery, Heidelberg University Hospital Schlierbacher Landstr. 200a, 69118 Heidelberg, Germany.

Gait & Posture
|December 14, 2020
PubMed
Summary
This summary is machine-generated.

Functional methods are recommended for estimating knee joint axis in clinical gait analysis (CGA). Regression methods show slight superiority for knee joint center prediction in CGA protocols.

Keywords:
Deterministic methodFunctional calibration methodsKnee joint parametersRegression methodSystematic review

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Area of Science:

  • Biomechanics
  • Clinical Gait Analysis
  • Motion Analysis

Background:

  • Marker-based clinical gait analysis (CGA) protocols aim to improve robustness and reliability.
  • Accurate determination of knee joint center (KJC) and knee joint axis (KJA) is crucial for CGA outcomes.
  • Research has focused on enhancing CGA protocol standards since the 1990s.

Purpose of the Study:

  • To systematically review the scientific literature for recommendations on determining knee joint parameters (KJP) for CGA protocols.
  • To identify optimal methods for KJC and KJA estimation in CGA.

Main Methods:

  • Systematic electronic literature search conducted in November 2018 across three databases.
  • Keywords included "functional approach/method/calibration" and "knee joint".
  • Analysis by four reviewers, quality assessment, and consideration of technical aspects like marker sets and functional movements.

Main Results:

  • Thirty-one papers were included, with an average quality score of 75%.
  • Functional methods were found to be superior or equivalent to predictive methods for KJA estimation.
  • A regression method demonstrated slightly better performance for KJC prediction.

Conclusions:

  • Calibration methods should be implemented in CGA when feasible.
  • Further research is needed to evaluate the in vivo range of motion (RoM) for reliable and repeatable CGA results.