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Department of Robotics and Mechatronics Engineering
Surgical Robotics & Augmented Reality Lab
1. Journal Articles
A Novel End-Effector Robot System Enabling to Monitor Upper-Extremity Posture during Robot-Aided Planar Reaching Movements
Hwang, Yeji
;
Lee, Seongpung
;
Hong, Jaesung
;
Kim, Jonghyun
Department of Robotics and Mechatronics Engineering
Surgical Robotics & Augmented Reality Lab
1. Journal Articles
Department of Robotics and Mechatronics Engineering
REL(Rehabilitation Engineering Laboratory)
1. Journal Articles
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Title
A Novel End-Effector Robot System Enabling to Monitor Upper-Extremity Posture during Robot-Aided Planar Reaching Movements
Issued Date
2020-04
Citation
Hwang, Yeji. (2020-04). A Novel End-Effector Robot System Enabling to Monitor Upper-Extremity Posture during Robot-Aided Planar Reaching Movements. IEEE Robotics and Automation Letters, 5(2), 3035–3041. doi: 10.1109/LRA.2020.2974453
Type
Article
Author Keywords
Rehabilitation robotics
;
human detection and tracking
;
end-effector type robot
;
reaching movement
Keywords
MOTOR FUNCTION IMPAIRMENT
;
KINEMATICS
;
TRACKING
;
SENSORS
;
STROKE
;
KINECT
ISSN
2377-3766
Abstract
End-effector type robots have been popularly applied to robot-aided therapy for rehabilitation purpose. However, those robots have a key drawback for the purpose: lack of the user's posture (joint angle) information. This letter proposes a novel end-effector rehabilitation robot system that contains a contactless motion sensor to monitor upper- extremity posture during robot-aided reaching exercise. The sensor allows the posture estimation without complicated procedures but has an inaccuracy problem such as occlusion and an unreliable segment length. Therefore, we developed a posture monitoring method, which is an analytical method without training procedure, based on the combined use of the information obtained from the sensor and the robot. Eight healthy subjects participated in the experiment with planar reaching exercise for validation. The results of joint angle estimation, high correlation coefficient (0.95 ± 0.03) and small errors (3.55 ± 0.70 deg), show that the proposed system can provide affordable upper-extremity posture estimation. © 2020 IEEE.
URI
http://hdl.handle.net/20.500.11750/11694
DOI
10.1109/LRA.2020.2974453
Publisher
Institute of Electrical and Electronics Engineers Inc.
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