作者
Chao Wang, Peter PK Chan, Ben MF Lam, Sizhong Wang, Janet H Zhang, Zoe YS Chan, Rosa HM Chan, Kevin KW Ho, Roy TH Cheung
发表日期
2020/3/5
期刊
IEEE Transactions on Neural Systems and Rehabilitation Engineering
卷号
28
期号
4
页码范围
888-894
出版商
IEEE
简介
Previous clinical studies have reported that gait retraining is an effective non-invasive intervention for patients with medial compartment knee osteoarthritis. These gait retraining programs often target a reduction in the knee adduction moment (KAM), which is a commonly used surrogate marker to estimate the loading in the medial compartment of the tibiofemoral joint. However, conventional evaluation of KAM requires complex and costly equipment for motion capture and force measurement. Gait retraining programs, therefore, are usually confined to a laboratory environment. In this study, machine learning techniques were applied to estimate KAM during walking with data collected from two low-cost wearable sensors. When compared to the traditional laboratory-based measurement, our mobile solution using artificial neural network (ANN) and XGBoost achieved an excellent agreement with R 2 of 0.956 and 0 …
引用总数
202020212022202320243717911
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