Robust Pattern Recognition Myoelectric Training for Improved Online Control within a 3D Virtual Environment

Richard B. Woodward, Levi J. Hargrove

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

1 Scopus citations

Abstract

It has been shown that maintaining a neutral arm position during collection of pattern recognition training data for myoelectric prosthesis control results in high offline classification accuracies; however, that precision does not translate to real-time applications, when the arm is used in different positions. Previous studies have shown that collecting training data with the arm in a variety of positions can improve pattern recognition control systems. In this work, we extended these findings to real-time myoelectric control in an immersive testing environment using virtual reality. We show that collecting training data for a pattern recognition algorithm under dynamic conditions, where the user moves their arm, significantly improves control efficiency and achievement of testing metrics.

Original languageEnglish (US)
Title of host publication40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4701-4704
Number of pages4
ISBN (Electronic)9781538636466
DOIs
StatePublished - Oct 26 2018
Event40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018 - Honolulu, United States
Duration: Jul 18 2018Jul 21 2018

Publication series

NameProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Volume2018-July
ISSN (Print)1557-170X

Other

Other40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2018
Country/TerritoryUnited States
CityHonolulu
Period7/18/187/21/18

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Fingerprint

Dive into the research topics of 'Robust Pattern Recognition Myoelectric Training for Improved Online Control within a 3D Virtual Environment'. Together they form a unique fingerprint.

Cite this