| Presentation | 2005-07-30 ニューラルネットワークを用いた鼾音の状態推定 / /, Udantha R Abeyratne, / /, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Snoring is the earliest and the most common symptom of Obstructive Sleep Apnea (OSA) which is a serious disease caused by the collapse of upper airways during sleep. Recently, a few pioneering attempts have been made to use snore sounds (SS) is diagnosing OSA. The SS are simple to acquire and rich in features but their analysis is complicated. In this paper, we propose a neural network (NN) based method to model SS via a technique associated with prediction. We also show that the features of a SS can be conveniently captured in the connection-weight-space (CWS) of the NN, after a process of supervised training. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | connection-weight-space / neural network / snoring sound |
| Paper # | MBE2005-51 |
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| Conference Information | |
| Committee | MBE |
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| Conference Date | 2005/7/23(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | ME and Bio Cybernetics (MBE) |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | |
| Sub Title (in English) | |
| Keyword(1) | connection-weight-space |
| Keyword(2) | neural network |
| Keyword(3) | snoring sound |
| 1st Author's Name | / / |
| 1st Author's Affiliation | () |
| 2nd Author's Name | Udantha R Abeyratne |
| 2nd Author's Affiliation | / School of info. Tech and Electrical Engineering, The University of Queensland |
| 3rd Author's Name | / / |
| 3rd Author's Affiliation | / |
| Date | 2005-07-30 |
| Paper # | MBE2005-51 |
| Volume (vol) | vol.105 |
| Number (no) | 222 |
| Page | pp.pp.- |
| #Pages | 4 |
| Date of Issue | |