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Characterization of an Electrorheological Fluid for Rehabilitation Robotics Applications

[+] Author Affiliations
Joseph R. Davidson, Hermano Igo Krebs

Massachusetts Institute of Technology (MIT), Cambridge, MA

Paper No. SMASIS2017-4009, pp. V002T04A022; 7 pages
doi:10.1115/SMASIS2017-4009
From:
  • ASME 2017 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
  • Volume 2: Modeling, Simulation and Control of Adaptive Systems; Integrated System Design and Implementation; Structural Health Monitoring
  • Snowbird, Utah, USA, September 18–20, 2017
  • Conference Sponsors: Aerospace Division
  • ISBN: 978-0-7918-5826-4
  • Copyright © 2017 by ASME

abstract

Compared to clinic-based systems, rehabilitation robots designed for home use could enable increased accessibility and intensity of therapy for stroke survivors. To move upper extremity rehabilitation robots from the clinic to the home, the designs must become smaller, lighter, and less complex. One path to reducing the size of the robot’s hardware is to replace conventional actuators with smaller designs utilizing the unique properties of smart materials. As a first step towards reducing the size of upper extremity rehabilitation robots, this paper presents results from a characterization study of a prototype electrorheological fluid. The fluid’s dynamic yield stress was first measured using a modified controlled stress rheometer. A testbed was then developed to analyze the mechanical performance of a custom brake filled with the fluid. System parameters measured included braking torque at varying electric field strengths as well as the fluid’s speed of response. Maximum torque output was 4.80 N-m at an electric field strength of 3 kV/mm. Experimental results also indicate that the fluid’s activation and relaxation times will enable sufficient control bandwidth for the desired application. However, non-linear effects, such as field-dependent hysteresis, are significant and may require compensation from the controller supervising interaction between the robot and patient.

Copyright © 2017 by ASME

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