Comparison of exoskeleton robots and end-effector robots on training methods and gait biomechanics

Pi-Ying Cheng, Po Ying Lai*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Rehabilitation robot positively improves walking ability of patients with gait disorders. Over the last decade, rehabilitation robot devices replaced the training of overground and treadmill. In this paper, our discussion focuses on exoskeleton robot and end-effector robot. The purpose of this study was to compare the training methods, gait Kinematic trajectories and muscle activity patterns on subjects when training on exoskeleton robot and end-effector robot.

Original languageEnglish
Title of host publicationIntelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings
Pages258-266
Number of pages9
EditionPART 1
DOIs
StatePublished - 7 Oct 2013
Event6th International Conference on Intelligent Robotics and Applications, ICIRA 2013 - Busan, Korea, Republic of
Duration: 25 Sep 201328 Sep 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume8102 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Conference on Intelligent Robotics and Applications, ICIRA 2013
CountryKorea, Republic of
CityBusan
Period25/09/1328/09/13

Keywords

  • end-effector robot
  • exoskeleton robot
  • Rehabilitation robot

Fingerprint Dive into the research topics of 'Comparison of exoskeleton robots and end-effector robots on training methods and gait biomechanics'. Together they form a unique fingerprint.

  • Cite this

    Cheng, P-Y., & Lai, P. Y. (2013). Comparison of exoskeleton robots and end-effector robots on training methods and gait biomechanics. In Intelligent Robotics and Applications - 6th International Conference, ICIRA 2013, Proceedings (PART 1 ed., pp. 258-266). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8102 LNAI, No. PART 1). https://doi.org/10.1007/978-3-642-40852-6-27