Evaluation of a 1-DOF Hand Exoskeleton for Neuromuscular Rehabilitation

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Scopus citations

Abstract

A low-cost 1-DOF hand exoskeleton for neuromuscular rehabilitation has been designed and assembled. It consists of a base equipped with a servo motor, an index finger part, and a thumb part, connected through three gears. The index part has a tri-axial load cell and an attached ring to measure the finger force. An admittance control paradigm was designed to provide intuitive control and positive force amplification to assist the user’s finger movement. To evaluate the effects of different control parameters on neuromuscular response of the fingers, we created an integrated exoskeleton-hand musculoskeletal model to virtually simulate and optimize the control loop. The exoskeleton is controlled by a proportional derivative controller that computes the motor torque to follow a desired joint angle of the index part, which is obtained from inverse kinematics of a virtual end-effector mass driven by the finger force. We conducted parametric simulations of the exoskeleton in action, driven by the user’s closing and opening finger motion, with different proportional gains, end-effector masses, and other coefficients. We compared the interaction forces between the index finger and the ring in both passive and active modes. The best performing assistive controller can reduce the force from around 1.45 N (in passive mode) to only around 0.52 N, more than 64% of reduction. As a result, the muscle activations of the flexors and extensors were reduced significantly. We also noted the admittance control paradigm is versatile and can also provide resistance (e.g. for strength training) by simply increasing the virtual end-effector mass.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computational Vision and Biomechanics
PublisherSpringer
Pages384-397
Number of pages14
DOIs
StatePublished - 2020

Publication series

NameLecture Notes in Computational Vision and Biomechanics
Volume36
ISSN (Print)2212-9391
ISSN (Electronic)2212-9413

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Mechanical Engineering
  • Computer Vision and Pattern Recognition
  • Computer Science Applications
  • Artificial Intelligence

Keywords

  • Hand exoskeleton
  • Musculoskeletal model
  • Neuromuscular rehabilitation

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