MyoTrack: Tracking Subject Participation in Robotic Rehabilitation using sEMG and IMU

Shrey Pareek, Hemanth Manjunath, Ehsan T. Esfahani, Thenkurussi Kesavadas

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

Abstract

In this paper, we present MyoTrack, a two-step classification routine that uses a wearable surface electromyography (sEMG) sensor to identify the level of subject participation during robot assisted rehabilitation. In the first step, we use sEMG activation as a measure of patient participation; stating that, high sEMG correlates with high participation. We then extract the subject's hand trajectory using the Myo's inertial measurement unit. The hand trajectory is compared with the robot's trajectory to identify whether the high muscle activity observed is due to the active participation of the subject in therapy or due to random gestures and motions. As the robot assistance considered in this paper can autonomously complete the therapy task without any subject participation, it is crucial to identify this participation level. We demonstrate that high muscle activation along with high similarity between the hand and robot end-effector trajectory is a reliable indicator of subject participation with an accuracy > 90% for the cases considered.

Original languageEnglish (US)
Title of host publication2019 International Symposium on Medical Robotics, ISMR 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538678251
DOIs
StatePublished - May 8 2019
Event2019 International Symposium on Medical Robotics, ISMR 2019 - Atlanta, United States
Duration: Apr 3 2019Apr 5 2019

Publication series

Name2019 International Symposium on Medical Robotics, ISMR 2019

Conference

Conference2019 International Symposium on Medical Robotics, ISMR 2019
Country/TerritoryUnited States
CityAtlanta
Period4/3/194/5/19

Keywords

  • assistive systems
  • electromyography
  • inertial measurement unit
  • robotic rehabilitation
  • stroke
  • tele-rehabilitation
  • wearable sensors

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

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