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강상훈

Kang, Sang Hoon
Robotics and Rehabilitation Engineering Lab.
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dc.citation.endPage 343 -
dc.citation.number 2 -
dc.citation.startPage 334 -
dc.citation.title IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING -
dc.citation.volume 22 -
dc.contributor.author Kang, Sang Hoon -
dc.contributor.author Lee, Song Joo -
dc.contributor.author Ren, Yupeng -
dc.contributor.author Zhang, Li-Qun -
dc.date.accessioned 2023-12-22T02:46:26Z -
dc.date.available 2023-12-22T02:46:26Z -
dc.date.created 2015-08-06 -
dc.date.issued 2014-03 -
dc.description.abstract The external knee adduction moment (EKAM) is associated with knee osteoarthritis (OA) in many aspects including presence, progression, and severity of knee OA. Despite of its importance, there is a lack of EKAM estimation methods that can provide patients with knee OA real-time EKAM biofeedback for training and clinical evaluations without using a motion analysis laboratory. A practical real-time EKAM estimation method, which utilizes kinematics measured by a simple six degree-of-freedom goniometer and kinetics measured by a multi-axis force sensor underneath the foot, was developed to provide real-time feedback of the EKAM to the patients during stepping on an elliptical trainer, which can potentially be used to control and alter the EKAM. High reliability (ICC(2,1): 0.9580) of the real-time EKAM estimation method was verified through stepping trials of seven subjects without musculoskeletal disorders. Combined with advantages of elliptical trainers including functional weight-bearing stepping and mitigation of impulsive forces, the real-time EKAM estimation method is expected to help patients with knee OA better control frontal plane knee loading and reduce knee OA development and progression. © 2013 IEEE. -
dc.identifier.bibliographicCitation IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, v.22, no.2, pp.334 - 343 -
dc.identifier.doi 10.1109/TNSRE.2013.2291203 -
dc.identifier.issn 1534-4320 -
dc.identifier.scopusid 2-s2.0-84896476916 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/13402 -
dc.identifier.url http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6665072 -
dc.identifier.wosid 000342078300014 -
dc.language 영어 -
dc.publisher IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC -
dc.title Real-time knee adduction moment feedback training using an elliptical trainer -
dc.type Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -

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