A wearable sensor system for knee adduction moment measurement

Knee adduction moment is a key parameter that links with the severity of knee osteoarthritis. However, assessment of the knee adduction moment is commonly implemented through the stationary measurement systems in a gait laboratory. The purpose of this study is to develop a wearable sensor system tha...

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Bibliographic Details
Published inRCAR : 2016 IEEE International Conference on Real-time Computing and Robotics : 6-10 June 2016 pp. 7 - 12
Main Authors Yang Shen, Tao Liu, Qingguo Li, Jingang Yi, Xiaoyu Xie, Bo Wen, Inoue, Yoshio
Format Conference Proceeding
LanguageEnglish
Japanese
Published IEEE 01.06.2016
Subjects
Biological neural networks
Foot
Force
Knee
Legged locomotion
Wearable sensors
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Summary:Knee adduction moment is a key parameter that links with the severity of knee osteoarthritis. However, assessment of the knee adduction moment is commonly implemented through the stationary measurement systems in a gait laboratory. The purpose of this study is to develop a wearable sensor system that can be used to estimate the knee adduction moment. A wearable sensor sock, composed of six pressure sensors, were developed using the pressure-sensitive electric conductive rubber. Based on the sensor sock measurements and the reference knee adduction moment obtained from the motion capture system (Vicon), we trained a neural network model to estimate the knee adduction moment. In our validation experiments on healthy subjects, the knee adduction moment can be accurately estimated with the trained neural network model.
DOI:10.1109/RCAR.2016.7783992