Evaluation of linear regression simultaneous myoelectric control using intramuscular EMG

Lauren H. Smith*, Todd A. Kuiken, Levi J. Hargrove

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

95 Scopus citations

Abstract

Goal: The objective of this study was to evaluate the ability of linear regression models to decode patterns of muscle coactivation from intramuscular electromyogram (EMG) and provide simultaneous myoelectric control of a virtual 3-DOF wrist/hand system. Performance was compared to the simultaneous control of conventional myoelectric prosthesis methods using intramuscular EMG (parallel dual-site control) - an approach that requires users to independently modulate individual muscles in the residual limb, which can be challenging for amputees. Methods: Linear regression control was evaluated in eight able-bodied subjects during a virtual Fitts' law task and was compared to performance of eight subjects using parallel dual-site control. An offline analysis also evaluated how different types of training data affected prediction accuracy of linear regression control. Results: The two control systems demonstrated similar overall performance; however, the linear regression method demonstrated improved performance for targets requiring use of all three DOFs, whereas parallel dual-site control demonstrated improved performance for targets that required use of only one DOF. Subjects using linear regression control could more easily activate multiple DOFs simultaneously, but often experienced unintended movements when trying to isolate individual DOFs. Offline analyses also suggested that the method used to train linear regression systems may influence controllability. Conclusion and Significance: Linear regression myoelectric control using intramuscular EMG provided an alternative to parallel dual-site control for 3-DOF simultaneous control at the wrist and hand. The two methods demonstrated different strengths in controllability, highlighting the tradeoff between providing simultaneous control and the ability to isolate individual DOFs when desired.

Original languageEnglish (US)
Article number7214240
Pages (from-to)737-746
Number of pages10
JournalIEEE Transactions on Biomedical Engineering
Volume63
Issue number4
DOIs
StatePublished - Apr 2016

Funding

This work was supported by the NINDS Award 1F31NS083166, the DARPA RE-NET Program administered through the Space and Naval Warfare Systems Center under Contract N66001-12-1-4029, and the Chicago Biomedical Consortium.

Keywords

  • Fitts' law
  • Intramuscular EMG
  • Myoelectric prostheses

ASJC Scopus subject areas

  • Biomedical Engineering

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