Cross-Individual Obstructive Obstructive Apnea Detection in Snoring Signals Using Hybrid Deep Neural Networks
Authors: 
Xu Lin, Yun Lu, Heng Li, Yukun Qian, Lianyu Zhou, Mingjiang WangAuthors Info & Claims
Article No.: 16, Pages 1 - 6
Abstract
Sleep apnea syndrome (SAS) is a common sleep problem, among which obstructive sleep apnea (OSA) is the most common. It is estimated that 936 million adults aged 30-69 years suffer from mild to severe obstructive sleep apnea that can result in poor sleep quality and even endanger their lives. In our study, 2051 OSA snoring fragments and 2271 normal snoring fragments were collected, and then the two were classified by the hybrid neural network. The most important innovation of this paper is the cross-individual snoring classification, which is different from the previous work, making the model more generalized. The experimental dataset was from 24 patients, the snores of 20 patients were used for the training model, and the snores of 4 people were used for the test. Finally, the accuracy of classification on the test set was 73.75%, and a portable snore classification platform is realized by using an embedded platform and edge computing.
References
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- Cross-Individual Obstructive Obstructive Apnea Detection in Snoring Signals Using Hybrid Deep Neural Networks
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Published In
December 2022
770 pages
ISBN:9781450398336
DOI:10.1145/3579654
Copyright © 2022 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 14 March 2023
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- Research-article
- Research
- Refereed limited
Funding Sources
- the Natural Science Foundation of Guangdong Province
- the Shenzhen Basic Research Program
- the Professional and Doctoral Scientific Research Foundation of Huizhou University
- the Research Project of Enhanced Independent Innovation Ability of Huizhou University
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ACAI 2022
ACAI 2022: 2022 5th International Conference on Algorithms, Computing and Artificial Intelligence
December 23 - 25, 2022
Sanya, China
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Overall Acceptance Rate 173 of 395 submissions, 44%
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