Comparison of Linear and Non-linear Dimension Reduction Techniques for Automatic Apnea Detection
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21460%2F19%3A00337045" target="_blank" >RIV/68407700:21460/19:00337045 - isvavai.cz</a>
Alternative codes found
RIV/00023752:_____/19:43920217
Result on the web
<a href="http://dx.doi.org/10.1109/EHB47216.2019.8969972" target="_blank" >http://dx.doi.org/10.1109/EHB47216.2019.8969972</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/EHB47216.2019.8969972" target="_blank" >10.1109/EHB47216.2019.8969972</a>
Alternative languages
Result language
angličtina
Original language name
Comparison of Linear and Non-linear Dimension Reduction Techniques for Automatic Apnea Detection
Original language description
Oronasal thermal sensor signal recording within sleeping period was analyzed in sense of detection of respiratory events. The goal was to evaluate what extent an up to date non-linear dimension reduction technique increases performance of apnea classification compared to classifications based on linear dimension reduction and raw data. Based on an extensive database of recordings in apneic patients, we concluded thatn a non-linear approach didn't lead to better classification performance in comparison with a linear decomposition technique. We suggested, that it was due to the signal amplitude is naturally the main feature of respiratory events. However, nonlinear methods do not naturally maintain the amplitude based structure in data. Due to this fact we get the worse signal representation in comparison with linear methods.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20601 - Medical engineering
Result continuities
Project
<a href="/en/project/GA17-20480S" target="_blank" >GA17-20480S: Temporal context in analysis of long-term non-stationary multidimensional signal</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IEEE E-HEALTH AND BIOENGINEERING EHB 2019
ISBN
978-1-7281-2603-6
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
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Publisher name
Gr. T. Popa University of Medicine and Pharmacy
Place of publication
Iasi
Event location
Iasi
Event date
Nov 21, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000558648300104