Comparing Evolvable Hardware to Conventional Classifiers for Electromyographic Prosthetic Hand Control
Created by W.Langdon from
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- @InProceedings{gl-gr-08,
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author = "Kyrre Glette and Thiemo Gruber and Paul Kaufmann and
Jim Torresen and Bernhard Sick and Marco Platzner",
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title = "Comparing Evolvable Hardware to Conventional
Classifiers for Electromyographic Prosthetic Hand
Control",
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booktitle = "2008 NASA/ESA Conference on Adaptive Hardware and
Systems",
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year = "2008",
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pages = "32--39",
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month = "22-25 " # jun,
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publisher = "IEEE",
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keywords = "genetic algorithms, genetic programming, Cartesian
Genetic Programming, ECGP, prosthetic hand control,
evolvable hardware, EHW, kNN, decision trees, DT,
support vector machines, SVM",
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isbn13 = "978-0-7695-3166-3",
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DOI = "doi:10.1109/AHS.2008.12",
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size = "8 pages",
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abstract = "Evolvable hardware has shown to be a promising
approach for prosthetic hand controllers as it features
self-adaptation, fast training, and a compact
system-on-chip implementation. Besides these intriguing
features, the classification performance is paramount
to success for any classifier. However, evolvable
hardware classifiers have not yet been sufficiently
compared to state-of-the-art conventional classifiers.
In this paper, we compare two evolvable hardware
approaches for signal classification to three
conventional classification techniques:
k-nearest-neighbour, decision trees, and support vector
machines. We provide all classifiers with features
extracted from electromyographic signals taken from
forearm muscle contractions, and try to recognise eight
different hand movements. Experimental results
demonstrate that evolvable hardware approaches are
indeed able to compete with state-of-the-art
classifiers. Specifically, one of our evolvable
hardware approaches delivers a generalisation
performance similar to that of support vector
machines.",
-
notes = "also known as \cite{4584252}",
- }
Genetic Programming entries for
Kyrre Harald Glette
Thiemo Gruber
Paul Kaufmann
Jim Torresen
Bernhard Sick
Marco Platzner
Citations