The design of a new upper limb rehabilitation robot system based on multi-source data fusion

Fancheng Meng*, Yaping Dai, Ying Jin, Yanni Wang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The aim of the paper is to develop a upper limb rehabilitation robot system (DPRs) capable of making both patient assessment and robot-aided assessment. Using the rehabilitation robot system, patients can repeatedly train in high efficiency and can replicate many of the human training. In the paper. First a diamond rehabilitation robot(DR)was designed and its model was also given. Then an evaluation unit to improve patient assessment based on multi-source data fusion tecnology was proposed, the evaluation unit mainly was used to yeild a qualititative value based on the quantitative analytical models, and then according to the qualititative value of the performance evaluation and active index, a resistance/assistance control strategy was designed to realize rehabilitation training more effectively. Finally the rehabilitation robot's control system was simulated and analyzed. Experiments showed that the DPRs purposed is helpful for the disabled patients and it can coordinate and train the patient's upper limb comfortingly and safely, and also has dynamic performance and high flexibility.

Original languageEnglish
Title of host publicationWCICA 2012 - Proceedings of the 10th World Congress on Intelligent Control and Automation
Pages3840-3845
Number of pages6
DOIs
Publication statusPublished - 2012
Event10th World Congress on Intelligent Control and Automation, WCICA 2012 - Beijing, China
Duration: 6 Jul 20128 Jul 2012

Publication series

NameProceedings of the World Congress on Intelligent Control and Automation (WCICA)

Conference

Conference10th World Congress on Intelligent Control and Automation, WCICA 2012
Country/TerritoryChina
CityBeijing
Period6/07/128/07/12

Keywords

  • Assistance
  • Clinica scale
  • Evaluation
  • Multi-source data fusion
  • Patient assessment
  • Resistance

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