@inproceedings{b758f17a9e32488b8efed9562fe9202e,
title = "Multimodal belief integration by HMM/SVM-embedded bayesian network: Applications to ambulating pc operation by body motions and brain signals",
abstract = "Methods to integrate multimodal beliefs by Bayesian Networks (BNs) comprising Hidden Markov Models (HMMs) and Support Vector Machines (SVMs) are presented. The integrated system is applied to the operation of ambulating PCs (biped humanoids) across the network. New features in this paper are twofold. First, the HMM/SVM-embedded BN for the multimodal belief integration is newly presented. Its subsystem also has a new structure such as a committee SVM array. Another new fearure is with the applications. Body and brain signals are applied to the ambulating PC operation by using the recognition of multimodal signal patterns. The body signals here are human gestures. Brain signals are either HbO2 of NIRS or neural spike trains. As for such ambulating PC operation, the total system shows better performance than HMM and BN systems alone.",
keywords = "Ambulating PC, Bayesian network, Committee SVM array, HMM, Multimodal beliefs",
author = "Yasuo Matsuyama and Fumiya Matsushima and Youichi Nishida and Takashi Hatakeyama and Nimiko Ochiai and Shogo Aida",
year = "2009",
doi = "10.1007/978-3-642-04274-4_79",
language = "English",
isbn = "3642042732",
volume = "5768 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "767--778",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
edition = "PART 1",
note = "19th International Conference on Artificial Neural Networks, ICANN 2009 ; Conference date: 14-09-2009 Through 17-09-2009",
}