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.
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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: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_43
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DOI: https://doi.org/10.1007/978-3-642-02490-0_43
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