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一种基于九轴惯性测量单元的新型膝关节冠状面不稳分类方法,用于内侧膝关节骨关节炎患者。

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

机构信息

Department of Orthopedic Surgery, Kita-Akita Municipal Hospital, Shimosugi, Kamishimizusawa 16-29, Kitaakita 018-4221, Japan.

Department of Orthopedic Surgery, Graduate School of Medicine, Akita University, Hondo 1-1-1, Akita 010-8543, Japan.

出版信息

Sensors (Basel). 2023 Mar 3;23(5):2797. doi: 10.3390/s23052797.

DOI:10.3390/s23052797
PMID:36905001
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10007345/
Abstract

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.

摘要

本研究旨在提出一种基于惯性运动传感器单元(IMU)步态分析的新型内翻推力分类方法,用于患有内侧膝关节骨关节炎(MKOA)的患者。我们使用九轴 IMU 研究了 69 个膝关节和 24 个(对照组)膝关节的大腿和小腿加速度。根据大腿和小腿节段的相对内外侧加速度矢量模式,我们将内翻推力分为四种表型:A型(大腿内侧,小腿内侧)、B 型(内侧,外侧)、C 型(外侧,内侧)和 D 型(外侧,外侧)。使用基于扩展卡尔曼滤波的算法计算定量内翻推力。我们比较了我们提出的 IMU 分类与 Kellgren-Lawrence(KL)分级对定量内翻推力和可见内翻推力的差异。在早期 OA 中,大多数内翻推力在视觉上不可察觉。在晚期 MKOA 中,观察到外侧大腿加速度的 C 型和 D 型比例增加。定量内翻推力从 A 型到 D 型逐渐增加。由于这种新型 IMU 分类能够检测到常规运动分析无法捕捉到的细微运动变化,因此具有更好的临床实用性,即使在 MKOA 的早期阶段也是如此。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/2b93d9b81b6c/sensors-23-02797-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/538dd1830adf/sensors-23-02797-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/7a68980153c0/sensors-23-02797-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/fb0585782d12/sensors-23-02797-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/6aefbd576e08/sensors-23-02797-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/2b93d9b81b6c/sensors-23-02797-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/538dd1830adf/sensors-23-02797-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/7a68980153c0/sensors-23-02797-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/fb0585782d12/sensors-23-02797-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/6aefbd576e08/sensors-23-02797-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bdc1/10007345/2b93d9b81b6c/sensors-23-02797-g005.jpg

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Diagnostic Accuracy of the Mobile Assessment of Varus Thrust Using Nine-axis Inertial Measurement Units.
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Prog Rehabil Med. 2021 Feb 6;6:20210009. doi: 10.2490/prm.20210009. eCollection 2021.
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