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Mobile Information Systems Volume 2017 ,2017-06-27
Design and Voluntary Motion Intention Estimation of a Novel Wearable Full-Body Flexible Exoskeleton Robot
Research Article
Chunjie Chen 1 , 2 , 3 Xinyu Wu 1 , 2 , 4 Du-xin Liu 1 , 2 , 3 Wei Feng 1 , 2 Can Wang 1 , 2
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DOI:10.1155/2017/8682168
Received 2017-01-28, accepted for publication 2017-03-30, Published 2017-03-30
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摘要

The wearable full-body exoskeleton robot developed in this study is one application of mobile cyberphysical system (CPS), which is a complex mobile system integrating mechanics, electronics, computer science, and artificial intelligence. Steel wire was used as the flexible transmission medium and a group of special wire-locking structures was designed. Additionally, we designed passive joints for partial joints of the exoskeleton. Finally, we proposed a novel gait phase recognition method for full-body exoskeletons using only joint angular sensors, plantar pressure sensors, and inclination sensors. The method consists of four procedures. Firstly, we classified the three types of main motion patterns: normal walking on the ground, stair-climbing and stair-descending, and sit-to-stand movement. Secondly, we segregated the experimental data into one gait cycle. Thirdly, we divided one gait cycle into eight gait phases. Finally, we built a gait phase recognition model based on k-Nearest Neighbor perception and trained it with the phase-labeled gait data. The experimental result shows that the model has a 98.52% average correct rate of classification of the main motion patterns on the testing set and a 95.32% average correct rate of phase recognition on the testing set. So the exoskeleton robot can achieve human motion intention in real time and coordinate its movement with the wearer.

授权许可

Copyright © 2017 Chunjie Chen et al. 2017
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

图表

Exoskeleton robot system structure.

Steel wire in one loop.

Steel wire transmissions.

Wire-locking pulley.

Passive spherical joint.

Passive spherical joint group.

Full-body flexible exoskeleton robot.

Sensor data acquisition system.

Plantar pressure sensor distribution.

Stair-climbing and stair-descending.

STS.

Human walking gait cycle.

Gait cycle cutting.

Gait phases in one cycle.

Gait phase recognition.

Distinguishing of normal walking and stair-climbing.

The best coefficient u.

The gait phase recognition results of four cycles acquired from four different subjects. KNN, gait phase recognition model.

The gait phase recognition results of four cycles acquired from four different subjects. KNN, gait phase recognition model.

The gait phase recognition results of four cycles acquired from four different subjects. KNN, gait phase recognition model.

The gait phase recognition results of four cycles acquired from four different subjects. KNN, gait phase recognition model.

通讯作者

1. Xinyu Wu.Guangdong Provincial Key Laboratory of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, cas.cn;Chinese Academy of Sciences (CAS) Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen 518055, China, cas.cn;Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Hong Kong, cuhk.edu.hk.xy.wu@siat.ac.cn
2. Can Wang.Guangdong Provincial Key Laboratory of Robotics and Intelligent System, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China, cas.cn;Chinese Academy of Sciences (CAS) Key Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen 518055, China, cas.cn.can.wang@siat.ac.cn

推荐引用方式

Chunjie Chen,Xinyu Wu,Du-xin Liu,Wei Feng,Can Wang. Design and Voluntary Motion Intention Estimation of a Novel Wearable Full-Body Flexible Exoskeleton Robot. Mobile Information Systems ,Vol.2017(2017)

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