Presentation | 2011-06-09 Stress state classification based on photoplethysmogram by supervised dimensionally reduction Ying LI, Keiichi HORIO, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | In this paper, we introduce a latent variables extraction method to improve a classification of stress states. Features obtained from a photoplethysmogram include various kinds of physical quantities, thus direct comparison between features causes degradation of classification. In this study, Multiple Relational Embedding (MRE) which reconstructs data distribution in low dimensional space based on similarity between data represented in some different measures is used. Furthermore class information of data can be used as one of the measure in MRE, then data distribution which is suitable for classification can be realized. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | stress state classification / photoplethysmogram / supervised dimensionality reduction |
Paper # | SIS2011-3 |
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Committee | SIS |
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Conference Date | 2011/6/2(1days) |
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Registration To | Smart Info-Media Systems (SIS) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Stress state classification based on photoplethysmogram by supervised dimensionally reduction |
Sub Title (in English) | |
Keyword(1) | stress state classification |
Keyword(2) | photoplethysmogram |
Keyword(3) | supervised dimensionality reduction |
1st Author's Name | Ying LI |
1st Author's Affiliation | Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology() |
2nd Author's Name | Keiichi HORIO |
2nd Author's Affiliation | Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology |
Date | 2011-06-09 |
Paper # | SIS2011-3 |
Volume (vol) | vol.111 |
Number (no) | 78 |
Page | pp.pp.- |
#Pages | 4 |
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