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강상훈

Kang, Sang Hoon
Robotics and Rehabilitation Engineering Lab.
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Real-time tracking of knee adduction moment in patients with knee osteoarthritis

Author(s)
Kang, Sang HoonLee, Song JooZhang, Li-Qun
Issued Date
2014-07
DOI
10.1016/j.jneumeth.2013.12.001
URI
https://scholarworks.unist.ac.kr/handle/201301/11401
Citation
JOURNAL OF NEUROSCIENCE METHODS, v.231, pp.9 - 17
Abstract
Background: The external knee adduction moment (EKAM) is closely associated with the presence, progression, and severity of knee osteoarthritis (OA). However, there is a lack of convenient and practical method to estimate and track in real-time the EKAM of patients with knee OA for clinical evaluation and gait training, especially outside of gait laboratories.

New method: A real-time EKAM estimation method was developed and applied to track and investigate the EKAM and other knee moments during stepping on an elliptical trainer in both healthy subjects and a patient with knee OA.

Results: Substantial changes were observed in the EKAM and other knee moments during stepping in the patient with knee OA.

Comparison with existing method(s): This is the first study to develop and test feasibility of real-time tracking method of the EKAM on patients with knee OA using 3-D inverse dynamics.

Conclusions: The study provides us an accurate and practical method to evaluate in real-time the critical EKAM associated with knee OA, which is expected to help us to diagnose and evaluate patients with knee OA and provide the patients with real-time EKAM feedback rehabilitation training. (C) 2013 Elsevier B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
ISSN
0165-0270

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