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A Novel Classification of Coronal Plane Knee Joint Instability Using Nine-Axis Inertial Measurement Units in Patients with Medial Knee Osteoarthritis.

Hiroaki TsukamotoKimio SaitoHidetomo SaitoHiroaki KijimaManabu AkagawaAkira KomatsuTakehiro IwamiNaohisa Miyakoshi
Published in: Sensors (Basel, Switzerland) (2023)
The purpose of this study was to propose a novel classification of varus thrust based on gait analysis with inertial motion sensor units (IMUs) in patients with medial knee osteoarthritis (MKOA). We investigated thigh and shank acceleration using a nine-axis IMU in 69 knees with MKOA and 24 (control) knees. We classified varus thrust into four phenotypes according to the relative medial-lateral acceleration vector patterns of the thigh and shank segments: pattern A (thigh medial, shank medial), pattern B (medial, lateral), pattern C (lateral, medial), and pattern D (lateral, lateral). Quantitative varus thrust was calculated using an extended Kalman filter-based algorithm. We compared the differences between our proposed IMU classification and the Kellgren-Lawrence (KL) grades for quantitative varus thrust and visible varus thrust. Most of the varus thrust was not visually perceptible in early-stage OA. In advanced MKOA, increased proportions of patterns C and D with lateral thigh acceleration were observed. Quantitative varus thrust was significantly increased stepwise from patterns A to D. This novel IMU classification has better clinical utility due to its ability to detect subtle kinematic changes that cannot be captured with conventional motion analysis even in the early stage of MKOA.
Keyphrases
  • knee osteoarthritis
  • early stage
  • machine learning
  • deep learning
  • minimally invasive
  • total knee arthroplasty
  • soft tissue
  • radiation therapy
  • lymph node
  • mass spectrometry
  • cerebral palsy
  • anterior cruciate ligament