Bio-signal integration for humanoid operation: Gesture and brain signal recognition by HMM/SVM-Embedded BN

Yasuo Matsuyama, Fumiya Matsushima, Youichi Nishida, Takashi Hatakeyama, Koji Sawada, Takatoshi Kato

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    Joint recognition of bio-signals emanated from human(s) is discussed. The bio-signals in this paper include camera-captured gestures and brain signals of hemoglobin change ΔO 2 H b . The recognition of the integrated data is applied to the operation of a biped humanoid. Hidden Markov Models (HMMs) and Support Vector Machines (SVMs) undertake the first stage recognition of individual signal. These subsystems are regarded as soft command issuers. Then, such low-level commands are integrated by a Bayesian Network (BN). Therefore, the total system is a novel HMM/SVM-embedded BN. Using this new recognition system, human operators can control the biped humanoid through the network by realizing more motion classes than methods of HMM-alone, SVM-alone and BN-alone.

    Original languageEnglish
    Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Pages352-360
    Number of pages9
    Volume5506 LNCS
    EditionPART 1
    DOIs
    Publication statusPublished - 2009
    Event15th International Conference on Neuro-Information Processing, ICONIP 2008 - Auckland
    Duration: 2008 Nov 252008 Nov 28

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 1
    Volume5506 LNCS
    ISSN (Print)03029743
    ISSN (Electronic)16113349

    Other

    Other15th International Conference on Neuro-Information Processing, ICONIP 2008
    CityAuckland
    Period08/11/2508/11/28

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

    Fingerprint Dive into the research topics of 'Bio-signal integration for humanoid operation: Gesture and brain signal recognition by HMM/SVM-Embedded BN'. Together they form a unique fingerprint.

  • Cite this

    Matsuyama, Y., Matsushima, F., Nishida, Y., Hatakeyama, T., Sawada, K., & Kato, T. (2009). Bio-signal integration for humanoid operation: Gesture and brain signal recognition by HMM/SVM-Embedded BN. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (PART 1 ed., Vol. 5506 LNCS, pp. 352-360). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5506 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-02490-0_43