Design and Voluntary Motion Intention Estimation of a Novel Wearable Full-Body Flexible Exoskeleton Robot
Joint Authors
Wang, Can
Chen, Chunjie
Liu, Du-xin
Feng, Wei
Wu, Xinyu
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-06-27
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Telecommunications Engineering
Abstract EN
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.
American Psychological Association (APA)
Chen, Chunjie& Wu, Xinyu& Liu, Du-xin& Feng, Wei& Wang, Can. 2017. Design and Voluntary Motion Intention Estimation of a Novel Wearable Full-Body Flexible Exoskeleton Robot. Mobile Information Systems،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1189232
Modern Language Association (MLA)
Chen, Chunjie…[et al.]. Design and Voluntary Motion Intention Estimation of a Novel Wearable Full-Body Flexible Exoskeleton Robot. Mobile Information Systems No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1189232
American Medical Association (AMA)
Chen, Chunjie& Wu, Xinyu& Liu, Du-xin& Feng, Wei& Wang, Can. Design and Voluntary Motion Intention Estimation of a Novel Wearable Full-Body Flexible Exoskeleton Robot. Mobile Information Systems. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1189232
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1189232