Skip Nav Destination
Close Modal
Update search
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
Filter
- Title
- Author
- Author Affiliations
- Full Text
- Abstract
- Keyword
- DOI
- ISBN
- ISBN-10
- ISSN
- EISSN
- Issue
- Journal Volume Number
- References
- Conference Volume Title
- Paper No
NARROW
Format
Article Type
Subject Area
Topics
Date
Availability
1-1 of 1
Keywords: apnea-hypopnea index (AHI)
Close
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Sort by
Journal Articles
Publisher: ASME
Article Type: Research-Article
ASME J of Medical Diagnostics. May 2024, 7(2): 021001.
Paper No: JESMDT-23-1031
Published Online: October 3, 2023
..., and calculates the apnea-hypopnea index (AHI). By analyzing the snoring signal in frequency domain, spectral entropy and other frequency-domain features are selected. Finally, the neural network classifier model is established. In the model, the input variables are eight frequency-domain features, and the output...
