Sleep apnea severity based on estimated tidal volume and snoring features from tracheal signals
Author:
Affiliation:
1. KITE, Toronto Rehabilitation Institute‐University Health Network Toronto ON Canada
2. Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto ON Canada
Funder
Ontario Centres of Excellence
Natural Sciences and Engineering Research Council of Canada
Publisher
Wiley
Subject
Behavioral Neuroscience,Cognitive Neuroscience,General Medicine
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1111/jsr.13490
Reference42 articles.
1. Obstructive sleep apnea screening by integrating snore feature classes
2. Pitch jump probability measures for the analysis of snoring sounds in apnea
3. Automatic and unsupervised snore sound extraction from respiratory sound signals;Azarbarzin A.;IEEE Transactions on Biomedical Engineering,2010
4. Snoring sounds variability as a signature of obstructive sleep apnea
5. Measurements and theory of normal tracheal breath sounds;Beck R.;Annals of Biomedical Engineering,2005
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