Please use this identifier to cite or link to this item:
Title: Step towards home-based robotic rehabilitation : an interface circuit for EEG : SEMG actuated orthosis
Authors: Gunadi Wihardjo.
Keywords: DRNTU::Engineering::Mechanical engineering::Assistive technology
Issue Date: 2009
Abstract: The world is faced with an urgent need for rehabilitation devices which fulfill clinical requirements, which are cheap, modular, versatile, compatible, easy to set up and monitored. In addition, the patient should be able to perform round-the-clock rehabilitation. The effectiveness of rehabilitation will be increased substantially (e.g. stroke patients) if the patients are able to use a robotic rehabilitation system at home, after having trained on it at the hospital. Due to high cost and complex architecture, most robotic orthoses are limited to use in the hospital. The “active” orthoses that make use of bio-signals for control purposes, are at present limited in their versatility, portability and usability. At the same time, studies show that rehabilitation speeds up when the level of patient engagement is higher. To make home-use a reality, it is of paramount importance that the system is low-cost, portable and simple to operate. The quality of bio-signal acquisition for an “active” robotic device must be good enough to enable stable, repeatable and reliable control signals. An acquisition and control system which satisfies these goals will create a significant impact on patient adoption of robotic rehabilitation devices. The sub-system design that is described in this paper is part of a wider research work to develop an accelerated stroke rehabilitation platform utilizing an EEG / SEMG based upper extremity robotic orthosis. This sub-system forms the “interface‟ between the patient and the computer / controlling device used for signal processing and orthosis control. Cost and weight is reduced significantly. The circuit can interface with industry standard data acquisition devices and switch seamlessly between surface electromyography (SEMG) and electroencephalography (EEG) operation. Test results are presented both with simulated signals as well as actual signals. It is also desired to interface the circuit to actuate the orthosis for rehabilitation purposes. This has been done with actual EEG / SEMG signal, which triggers the motor whenever it detects RMS value above any specified value. The motor subsequently drive the orthosis. Based on the findings of experiments conducted, further work on servo motor control can be done. Further work includes choosing better servo motor with less jerk, low cost, high torque, and high reability. One can also make a program which serves as best interface for patient and for therapist, with low complexity and high reability. The user should be able to understand the program easily, and able to choose which mode he wants to use. In addition, ultimate goal is to increase the portability of the machine to another level. It can be done by using wireless technology, or by changing the technology used in PCB (from THT to SMT), and many more. This project has produced a paper to the forthcoming International Conference in Advance Intelligent Mechatronics (AIM) 2009. A copy of the paper is attached in appendix A of the report.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:MAE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
  Restricted Access
Main Report2.12 MBAdobe PDFView/Open
Appendix A.pdf
  Restricted Access
Appendix A526.6 kBAdobe PDFView/Open
Appendix B.pdf
  Restricted Access
Appendix B72.22 kBAdobe PDFView/Open
Appendix C.pdf
  Restricted Access
Appendix C108.9 kBAdobe PDFView/Open
Appendix D.pdf
  Restricted Access
Appendix D106.11 kBAdobe PDFView/Open
Appendix E.pdf
  Restricted Access
Appendix E68.65 kBAdobe PDFView/Open
Appendix F.pdf
  Restricted Access
Appendix F55.56 kBAdobe PDFView/Open
Appendix G.pdf
  Restricted Access
Appendix G340.31 kBAdobe PDFView/Open

Page view(s) 50

Updated on Oct 18, 2021

Download(s) 50

Updated on Oct 18, 2021

Google ScholarTM


Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.