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airflow
National Institutes of Health
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Papers overview
Semantic Scholar uses AI to extract papers important to this topic.
2018
2018
Deep Neural Networks with Weighted Averaged Overnight Airflow Features for Sleep Apnea-Hypopnea Severity Classification
Payongkit Lakhan
,
Apiwat Ditthapron
,
Nannapas Banluesombatkul
,
Theerawit Wilaiprasitporn
IEEE Region 10 Conference
2018
Corpus ID: 67874196
Dramatic raising of Deep Learning (DL) approach and its capability in biomedical applications lead us to explore the advantages…
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2017
2017
New CFD tools to evaluate nasal airflow
M. A. Burgos
,
E. Sanmiguel-Rojas
,
C. del Pino
,
M. A. Sevilla-García
,
F. Esteban-Ortega
European Archives of Oto-Rhino-Laryngology
2017
Corpus ID: 3733940
Computational fluid dynamics (CFD) is a mathematical tool to analyse airflow. As currently CFD is not a usual tool for…
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Highly Cited
2016
Highly Cited
2016
Utility of AdaBoost to Detect Sleep Apnea-Hypopnea Syndrome From Single-Channel Airflow
G. Gutiérrez-Tobal
,
D. Álvarez
,
F. Campo
,
R. Hornero
IEEE Transactions on Biomedical Engineering
2016
Corpus ID: 22277920
Goal: The purpose of this study is to evaluate the usefulness of the boosting algorithm AdaBoost (AB) in the context of the sleep…
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2016
2016
SAHS Detection Based on ANFIS Using Single Channel Airflow Signal
M. Paul
,
Amithab
2016
Corpus ID: 212548261
The aim of this paper is to present an efficient and accurate detection algorithm for Sleep ApneaHypopnea syndrome (SAHS) based…
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2016
2016
Computational fluid dynamics benchmark dataset of airflow in tracheas
A. Bates
,
A. Comerford
,
R. Cetto
,
D. Doorly
,
R. Schroter
,
N. Tolley
Data in Brief
2016
Corpus ID: 18187603
2015
2015
Phonatory aerodynamics in connected speech
Jackie L. Gartner-Schmidt
,
R. Hirai
,
Christina Dastolfo
,
C. Rosen
,
Lan Yu
,
A. Gillespie
The Laryngoscope
2015
Corpus ID: 20178232
1) Present phonatory aerodynamic data for healthy controls (HCs) in connected speech; 2) contrast these findings between HCs and…
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2013
2013
Pattern recognition in airflow recordings to assist in the sleep apnoea–hypopnoea syndrome diagnosis
G. Gutiérrez-Tobal
,
D. Álvarez
,
J. Victor Marcos
,
F. Campo
,
R. Hornero
Medical and Biological Engineering and Computing
2013
Corpus ID: 14236935
Abstract This paper aims at detecting sleep apnoea–hypopnoea syndrome (SAHS) from single-channel airflow (AF) recordings. The…
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2012
2012
Linear and nonlinear analysis of airflow recordings to help in sleep apnoea–hypopnoea syndrome diagnosis
G. Gutiérrez-Tobal
,
R. Hornero
,
D. Álvarez
,
J. Victor Marcos
,
F. del Campo
Physiological Measurement
2012
Corpus ID: 45219119
This paper focuses on the analysis of single-channel airflow (AF) signal to help in sleep apnoea–hypopnoea syndrome (SAHS…
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Highly Cited
2008
Highly Cited
2008
Comparison of Respiratory Rates Derived from Heart Rate Variability, ECG Amplitude, and Nasal/Oral Airflow
D. Cysarz
,
R. Zerm
,
H. Bettermann
,
M. Frühwirth
,
M. Moser
,
M. Kröz
Annals of Biomedical Engineering
2008
Corpus ID: 20167601
It would often be desirable to obtain the respiratory rate during everyday conditions without obtaining an additional respiratory…
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2005
2005
Restorative procedures in disturbed function of the upper airways - nasal breathing
G. Mlynski
GMS current topics in otorhinolaryngology, head…
2005
Corpus ID: 13529757
These days, functional rhinosurgery is almost always taken to mean the improvement of nasal airflow. However, air should not only…
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