A Comparison of Surface and Intramuscular Myoelectric Signal Classification

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...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 2007-05, Vol.54 (5), p.847-853
Main Authors: Hargrove, Levi J., Englehart, Kevin, Hudgins, Bernard
Format: Article
Language:English
Subjects:
Accuracy
Adult
Biomedical signal processing
Classification
Control systems
Data mining
Elbow
Electric Impedance
Electrodes
Electromyography - methods
EMG
Feature extraction
Forearm - anatomy & histology
Forearm - physiology
Hand - physiology
Humans
intramuscular
Isometric Contraction - physiology
Male
Measurement techniques
Models, Biological
Muscle, Skeletal - physiology
myoelectric
Pattern classification
Pattern recognition
Pattern Recognition, Physiological
prostheses
Prosthetics
Signal Processing, Computer-Assisted
Software
Studies
Technological innovation
Wrist - physiology
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Summary: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
ISSN:0018-9294
1558-2531
DOI:10.1109/TBME.2006.889192