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

1Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.
Get full text

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. © 2009 Springer Berlin Heidelberg.

Cite

CITATION STYLE

APA

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) (Vol. 5506 LNCS, pp. 352–360). https://doi.org/10.1007/978-3-642-02490-0_43

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free