TY - GEN
T1 - A gait retraining feedback system based on wearable sensors
AU - He, Zexia
AU - Shen, Yang
AU - Liu, Tao
AU - Yi, Jingang
AU - Ferreira, João Paulo
N1 - Funding Information:
*This work was supported in part by the NSFC Grant No. 61428304, Zhejiang Provincial Natural Science Foundation of China under Grant No. LR15E050002. We thank Fundação para a Ciência e a Tecnologia(FCT) and COMPETE 2020 program for the financial support to the project “Automatic Adaptation of an Humanoid Robot Gait to Different Floor-Robot Friction Coefficients” (PTDC/EEI-AUT/5141/2014).
Publisher Copyright:
© 2017 IEEE.
PY - 2017/8/21
Y1 - 2017/8/21
N2 - The purpose of this study is to develop a gait retraining feedback system based on wearable sensors for the gait training and the recovery of knee osteoarthritis patients. The system is mainly composed of one motion sensor, six plantar pressure sensors, vibrator and upper computer. The foot progression angle of subject measured by the motion sensor was transmitted to a upper computer through a WIFI module. The judgment for foot progression angle by PC was then sent to the motion sensor for the feedback of gait retraining by a vibrator. In order to validate the training effect of the system, walking experiments of simulated patients was conducted. The results show that the gait retraining system can have a effective influence on the gait in real time and can be used to train the walking gait to reduce the knee adduction moment.
AB - The purpose of this study is to develop a gait retraining feedback system based on wearable sensors for the gait training and the recovery of knee osteoarthritis patients. The system is mainly composed of one motion sensor, six plantar pressure sensors, vibrator and upper computer. The foot progression angle of subject measured by the motion sensor was transmitted to a upper computer through a WIFI module. The judgment for foot progression angle by PC was then sent to the motion sensor for the feedback of gait retraining by a vibrator. In order to validate the training effect of the system, walking experiments of simulated patients was conducted. The results show that the gait retraining system can have a effective influence on the gait in real time and can be used to train the walking gait to reduce the knee adduction moment.
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U2 - 10.1109/AIM.2017.8014154
DO - 10.1109/AIM.2017.8014154
M3 - Conference contribution
AN - SCOPUS:85028753767
T3 - IEEE/ASME International Conference on Advanced Intelligent Mechatronics, AIM
SP - 1029
EP - 1034
BT - 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Advanced Intelligent Mechatronics, AIM 2017
Y2 - 3 July 2017 through 7 July 2017
ER -