Position Error-Based Identification of Subject Participation in Robotic-Rehabilitation

Shrey Pareek, Pramod Chembrammel, John K. Nguyen, Thenkurussi Kesavadas

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

Abstract

In this paper, we present a haptics-based rehabilitation system that uses kinematics of a haptic device to monitor a subject's participation in therapy. In robot-assisted therapy, it is crucial to monitor if the patient is actively performing the rehabilitation task and is not just passively following the robot's motions. In this paper, we have used position-tracking error patterns as a metric for identifying whether the subject is actively participating in the therapy. Using a single feature identification scheme, our method demonstrated a real-time classification accuracy of 80.04% in separating active and passive participation during a therapy session.

Original languageEnglish (US)
Title of host publicationBIOROB 2018 - 7th IEEE International Conference on Biomedical Robotics and Biomechatronics
PublisherIEEE Computer Society
Pages432-438
Number of pages7
ISBN (Electronic)9781538681831
DOIs
StatePublished - Oct 9 2018
Event7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018 - Enschede, Netherlands
Duration: Aug 26 2018Aug 29 2018

Publication series

NameProceedings of the IEEE RAS and EMBS International Conference on Biomedical Robotics and Biomechatronics
Volume2018-August
ISSN (Print)2155-1774

Other

Other7th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics, BIOROB 2018
Country/TerritoryNetherlands
CityEnschede
Period8/26/188/29/18

ASJC Scopus subject areas

  • Artificial Intelligence
  • Biomedical Engineering
  • Mechanical Engineering

Fingerprint

Dive into the research topics of 'Position Error-Based Identification of Subject Participation in Robotic-Rehabilitation'. Together they form a unique fingerprint.

Cite this