Nocturnal sleep sounds classification with artificial neural network for sleep monitoring
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Link
https://link.springer.com/content/pdf/10.1007/s11042-023-16190-3.pdf
Reference19 articles.
1. Adesuyi TA, Kim BM, Kim J (2022) Snoring sound classification using 1D-CNN model based on multi-feature extraction. Int J Fuzzy Logic Intell Syst 22(1):1–10. https://doi.org/10.5391/IJFIS.2022.22.1.1
2. Akbal E, Tuncer T (2021) FusedTSNet: An automated nocturnal sleep sound classification method based on a fused textural and statistical feature generation network. Appl Acoust 171:107559. https://doi.org/10.1016/j.apacoust.2020.107559
3. Alías F, Socoró JC, Sevillano X (2016) A review of physical and perceptual feature extraction techniques for speech, music and environmental sounds. Appl Sci 6:5. https://doi.org/10.3390/app6050143
4. Amoh J, Odame K (2016) Artificial Neural Networks for identifying cough sounds. IEEE Trans Biomed Circuits Syst 10(5):1003–1011
5. Chang X, Peng C, Xing G, Hao T, Zhou G (2020) iSleep: A Smartphone System for Unobtrusive Sleep Quality Monitoring. ACM Trans Sens Netw (TOSN) 16(3):1–32
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