Real-time knee adduction moment feedback training using an elliptical trainer

Sang Hoon Kang, Song Joo Lee, Yupeng Ren, Li Qun Zhang

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

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.

Original languageEnglish (US)
Article number6665072
Pages (from-to)334-343
Number of pages10
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
Volume22
Issue number2
DOIs
StatePublished - Mar 2014

Keywords

  • Center of pressure (COP)
  • Real-time biofeedback
  • knee adduction moment
  • knee osteoarthritis (OA)

ASJC Scopus subject areas

  • Internal Medicine
  • Neuroscience(all)
  • Biomedical Engineering

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