Literature DB >> 17518281

A comparison of surface and intramuscular myoelectric signal classification.

Levi J Hargrove1, Kevin Englehart, Bernard Hudgins.   

Abstract

The surface myoelectric signal (MES) has been used as an input to controllers for powered prostheses for many years. As a result of recent technological advances it is reasonable to assume that there will soon be implantable myoelectric sensors which will enable the internal MES to be used as input to these controllers. An internal MES measurement should have less muscular crosstalk allowing for more independent control sites. However, it remains unclear if this benefit outweighs the loss of the more global information contained in the surface MES. This paper compares the classification accuracy of six pattern recognition-based myoelectric controllers which use multi-channel surface MES as inputs to the same controllers which use multi-channel intramuscular MES as inputs. An experiment was designed during which surface and intramuscular MES were collected simultaneously for 10 different classes of isometric contraction. There was no significant difference in classification accuracy as a result of using the intramuscular MES measurement technique when compared to the surface MES measurement technique. Impressive classification accuracy (97%) could be achieved by optimally selecting only three channels of surface MES.

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Year:  2007        PMID: 17518281     DOI: 10.1109/TBME.2006.889192

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  81 in total

1.  Real-time simultaneous and proportional myoelectric control using intramuscular EMG.

Authors:  Lauren H Smith; Todd A Kuiken; Levi J Hargrove
Journal:  J Neural Eng       Date:  2014-11-14       Impact factor: 5.379

2.  Improving myoelectric pattern recognition robustness to electrode shift by changing interelectrode distance and electrode configuration.

Authors:  Aaron J Young; Levi J Hargrove; Todd A Kuiken
Journal:  IEEE Trans Biomed Eng       Date:  2011-11-29       Impact factor: 4.538

3.  Target Achievement Control Test: evaluating real-time myoelectric pattern-recognition control of multifunctional upper-limb prostheses.

Authors:  Ann M Simon; Levi J Hargrove; Blair A Lock; Todd A Kuiken
Journal:  J Rehabil Res Dev       Date:  2011

4.  Electromyogram-based neural network control of transhumeral prostheses.

Authors:  Christopher L Pulliam; Joris M Lambrecht; Robert F Kirsch
Journal:  J Rehabil Res Dev       Date:  2011

5.  Subject-specific myoelectric pattern classification of functional hand movements for stroke survivors.

Authors:  Sang Wook Lee; Kristin M Wilson; Blair A Lock; Derek G Kamper
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-09-27       Impact factor: 3.802

6.  An analysis of EMG electrode configuration for targeted muscle reinnervation based neural machine interface.

Authors:  He Huang; Ping Zhou; Guanglin Li; Todd A Kuiken
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2008-02       Impact factor: 3.802

7.  Adaptive pattern recognition of myoelectric signals: exploration of conceptual framework and practical algorithms.

Authors:  Jonathon W Sensinger; Blair A Lock; Todd A Kuiken
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2009-06-02       Impact factor: 3.802

8.  Decoding individuated finger flexions with Implantable MyoElectric Sensors.

Authors:  Justin J Baker; Dimitri Yatsenko; Jack F Schorsch; Glenn A DeMichele; Phil R Troyk; Douglas T Hutchinson; Richard F ff Weir; Gregory Clark; Bradley Greger
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2008

9.  A novel myoelectric pattern recognition strategy for hand function restoration after incomplete cervical spinal cord injury.

Authors:  Jie Liu; Ping Zhou
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2012-09-27       Impact factor: 3.802

10.  Classification of simultaneous movements using surface EMG pattern recognition.

Authors:  Aaron J Young; Lauren H Smith; Elliott J Rouse; Levi J Hargrove
Journal:  IEEE Trans Biomed Eng       Date:  2012-12-10       Impact factor: 4.538

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