Development of a Series Elastic Elbow Neurological Exam Training Simulator for Lead-pipe Rigidity

Kevin G. Gim, Maxine He, Mahshid Mansouri, Yinan Pei, Evan Ripperger, Christopher M. Zallek, Elizabeth T. Hsiao-Wecksler

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

Abstract

This paper describes the development of a 1-DOF kinesthetic force display device in the form of an arm training simulator that replicates the haptic feeling of lead-pipe rigidity in the elbow joint. Patients with lead-pipe rigidity have uniformly elevated muscle tone throughout the range of motion, which is an important clinical sign for diagnosing Parkinson's disease during a neurological examination. The simulator could provide training opportunities for healthcare trainees to learn and practice the assessment technique for lead-pipe rigidity. The simulator was driven by a series elastic actuator in order to have more accurate joint torque control in a safe and cost-effective manner for rendering abnormal muscle resistance. A mathematical model of lead-pipe rigidity based on hyperbolic tangent was proposed to recreate the elevated muscle resistance at different Unified Parkinson's Disease Rating Scale (UPDRS) 0-3. Performance of the simulator was evaluated through benchtop tests and rigidity simulation tests. Preliminary results suggested the simulator had good torque control accuracy (an average RMSE < 0.27 Nm) and good fidelity in mimicking clinically-measured lead-pipe rigidity at UPDRS 0-3.

Original languageEnglish (US)
Title of host publication2021 IEEE International Conference on Robotics and Automation, ICRA 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages10340-10346
Number of pages7
ISBN (Electronic)9781728190778
DOIs
StatePublished - 2021
Externally publishedYes
Event2021 IEEE International Conference on Robotics and Automation, ICRA 2021 - Xi'an, China
Duration: May 30 2021Jun 5 2021

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2021-May
ISSN (Print)1050-4729

Conference

Conference2021 IEEE International Conference on Robotics and Automation, ICRA 2021
Country/TerritoryChina
CityXi'an
Period5/30/216/5/21

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Development of a Series Elastic Elbow Neurological Exam Training Simulator for Lead-pipe Rigidity'. Together they form a unique fingerprint.

Cite this