Simultaneous and proportional control of 2D wrist movements with myoelectric signals

J. M. Hahne, H. Rehbaum, F. Biessmann, F. C. Meinecke, K. R. Muller, N. Jiang, D. Farina, L. C. Parra

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

34 Citations (Scopus)

Abstract

Previous approaches for extracting real-time proportional control information simultaneously for multiple degree of Freedom(DoF) from the electromyogram (EMG) often used non-linear methods such as the multilayer perceptron (MLP). In this pilot study we show that robust control is also possible with conventional linear regression if EMG power measures are available for a large number of electrodes. In particular, we show that it is possible to linearize the problem with simple nonlinear transformations of band-pass power. Because of its simplicity the method scales well to high dimensions, is easily regularized when insufficient training data is available, and is particularly well suited for real-time control as well as on-line optimization.

Original languageEnglish
Title of host publication2012 IEEE International Workshop on Machine Learning for Signal Processing - Proceedings of MLSP 2012
DOIs
Publication statusPublished - 2012
Event2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012 - Santander, Spain
Duration: 2012 Sept 232012 Sept 26

Publication series

NameIEEE International Workshop on Machine Learning for Signal Processing, MLSP
ISSN (Print)2161-0363
ISSN (Electronic)2161-0371

Other

Other2012 22nd IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2012
Country/TerritorySpain
CitySantander
Period12/9/2312/9/26

Keywords

  • Electromyography (EMG)
  • linear regression
  • myoelectric control
  • simultaneous control
  • upper limb prosthesis

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing

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