Fluctuating EMG Signals: Investigating Long-term Effects of Pattern Matching Algorithms

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Paul Kaufmann and Kevin Englehart and Marco Platzner",
  title =        "Fluctuating EMG Signals: Investigating Long-term
                 Effects of Pattern Matching Algorithms",
  booktitle =    "32nd Annual International Conference of the IEEE
                 Engineering in Medicine and Biology (EMBC 2010)",
  year =         "2010",
  pages =        "6357--6360",
  address =      "Buenos Aires, Argentina",
  month =        aug # " 31 - " # sep # " 4",
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/IEMBS.2010.5627288",
  size =         "4 pages",
  abstract =     "In this paper, we investigate the behaviour of
                 state-of-the-art pattern matching algorithms when
                 applied to electromyographic data recorded during 21
                 days. To this end, we compare the five classification
                 techniques k-nearest-neighbour, linear discriminant
                 analysis, decision trees, artificial neural networks
                 and support vector machines. We provide all classifiers
                 with features extracted from electromyographic signals
                 taken from forearm muscle contractions, and try to
                 recognize ten different hand movements. The major
                 result of our investigation is that the classification
                 accuracy of initially trained pattern matching
                 algorithms might degrade on subsequent data indicating
                 variations in the electromyographic signals over
  notes =        "Also known as \cite{5627288}",

Genetic Programming entries for Paul Kaufmann Kevin Englehart Marco Platzner