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Comparison of Statistical and Non-statistical Classifiers for Thumb Motion Clasification

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F08%3A03144957" target="_blank" >RIV/68407700:21230/08:03144957 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    čeština

  • Original language name

    Comparison of Statistical and Non-statistical Classifiers for Thumb Motion Clasification

  • Original language description

    This paper deals with a comparison of statistical and non-statistical classifiers for thumb motion classification. Presented work is a part of research of relation between brain and muscle activity. The thumb motion is represented by trajectory coordinates of special mark placed on the thumb. Motions are classified using k-Means classifier (non-statistical classification, no prior information is needed) and Bayes classifier (statistical models of classes are needed, classifier training is necessary). The efficiency of classifiers is evaluated using the standard HTK parameters. Real testing data includes more than 900 stationary states which are used for classifier testing. The classification results are compared for both methods.

  • Czech name

    Comparison of Statistical and Non-statistical Classifiers for Thumb Motion Clasification

  • Czech description

    This paper deals with a comparison of statistical and non-statistical classifiers for thumb motion classification. Presented work is a part of research of relation between brain and muscle activity. The thumb motion is represented by trajectory coordinates of special mark placed on the thumb. Motions are classified using k-Means classifier (non-statistical classification, no prior information is needed) and Bayes classifier (statistical models of classes are needed, classifier training is necessary). The efficiency of classifiers is evaluated using the standard HTK parameters. Real testing data includes more than 900 stationary states which are used for classifier testing. The classification results are compared for both methods.

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    JA - Electronics and optoelectronics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2008

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Lékař a technika

  • ISSN

    0301-5491

  • e-ISSN

  • Volume of the periodical

    38

  • Issue of the periodical within the volume

    2

  • Country of publishing house

    CZ - CZECH REPUBLIC

  • Number of pages

    3

  • Pages from-to

  • UT code for WoS article

  • EID of the result in the Scopus database