168 related articles for article (PubMed ID: 35853400)
1. A multi-modal assessment of sleep stages using adaptive Fourier decomposition and machine learning.
Fatimah B; Singhal A; Singh P
Comput Biol Med; 2022 Sep; 148():105877. PubMed ID: 35853400
[TBL] [Abstract][Full Text] [Related]
2. Sleep stage classification using covariance features of multi-channel physiological signals on Riemannian manifolds.
Jiang D; Ma Y; Wang Y
Comput Methods Programs Biomed; 2019 Sep; 178():19-30. PubMed ID: 31416548
[TBL] [Abstract][Full Text] [Related]
3. Machine learning-empowered sleep staging classification using multi-modality signals.
Satapathy SK; Brahma B; Panda B; Barsocchi P; Bhoi AK
BMC Med Inform Decis Mak; 2024 May; 24(1):119. PubMed ID: 38711099
[TBL] [Abstract][Full Text] [Related]
4. Sleep stage classification using single-channel EOG.
Rahman MM; Bhuiyan MIH; Hassan AR
Comput Biol Med; 2018 Nov; 102():211-220. PubMed ID: 30170769
[TBL] [Abstract][Full Text] [Related]
5. An End-to-End Multi-Channel Convolutional Bi-LSTM Network for Automatic Sleep Stage Detection.
Toma TI; Choi S
Sensors (Basel); 2023 May; 23(10):. PubMed ID: 37430865
[TBL] [Abstract][Full Text] [Related]
6. Automatic sleep stage classification based on a two-channel electrooculogram and one-channel electromyogram.
Li Y; Xu Z; Zhang Y; Cao Z; Chen H
Physiol Meas; 2022 Jul; 43(7):. PubMed ID: 35487205
[No Abstract] [Full Text] [Related]
7. [Multi-modal physiological time-frequency feature extraction network for accurate sleep stage classification].
Hu K; Chen J; Zhang P; Xue W; Xie J
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2024 Feb; 41(1):26-33. PubMed ID: 38403601
[TBL] [Abstract][Full Text] [Related]
8. Multivariate analysis of full-term neonatal polysomnographic data.
Gerla V; Paul K; Lhotska L; Krajca V
IEEE Trans Inf Technol Biomed; 2009 Jan; 13(1):104-10. PubMed ID: 19129029
[TBL] [Abstract][Full Text] [Related]
9. Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.
Zhang Z; Lin BS; Peng CW; Lin BS
IEEE Trans Neural Syst Rehabil Eng; 2024; 32():2096-2105. PubMed ID: 38848223
[TBL] [Abstract][Full Text] [Related]
10. An Automated Wavelet-Based Sleep Scoring Model Using EEG, EMG, and EOG Signals with More Than 8000 Subjects.
Sharma M; Yadav A; Tiwari J; Karabatak M; Yildirim O; Acharya UR
Int J Environ Res Public Health; 2022 Jun; 19(12):. PubMed ID: 35742426
[TBL] [Abstract][Full Text] [Related]
11. Multimodal analysis of electroencephalographic and electrooculographic signals.
ElSayed NE; Tolba AS; Rashad MZ; Belal T; Sarhan S
Comput Biol Med; 2021 Oct; 137():104809. PubMed ID: 34517160
[TBL] [Abstract][Full Text] [Related]
12. An effective hybrid feature selection using entropy weight method for automatic sleep staging.
Wang W; Li J; Fang Y; Zheng Y; You F
Physiol Meas; 2023 Oct; 44(10):. PubMed ID: 37783214
[No Abstract] [Full Text] [Related]
13. Automatic sleep staging using multi-dimensional feature extraction and multi-kernel fuzzy support vector machine.
Zhang Y; Zhang X; Liu W; Luo Y; Yu E; Zou K; Liu X
J Healthc Eng; 2014; 5(4):505-20. PubMed ID: 25516130
[TBL] [Abstract][Full Text] [Related]
14. Estimation of sleep stages by an artificial neural network employing EEG, EMG and EOG.
Tagluk ME; Sezgin N; Akin M
J Med Syst; 2010 Aug; 34(4):717-25. PubMed ID: 20703927
[TBL] [Abstract][Full Text] [Related]
15. Learning machines and sleeping brains: Automatic sleep stage classification using decision-tree multi-class support vector machines.
Lajnef T; Chaibi S; Ruby P; Aguera PE; Eichenlaub JB; Samet M; Kachouri A; Jerbi K
J Neurosci Methods; 2015 Jul; 250():94-105. PubMed ID: 25629798
[TBL] [Abstract][Full Text] [Related]
16. Multi-channel EEG-based sleep stage classification with joint collaborative representation and multiple kernel learning.
Shi J; Liu X; Li Y; Zhang Q; Li Y; Ying S
J Neurosci Methods; 2015 Oct; 254():94-101. PubMed ID: 26192325
[TBL] [Abstract][Full Text] [Related]
17. A novel, fast and efficient single-sensor automatic sleep-stage classification based on complementary cross-frequency coupling estimates.
Dimitriadis SI; Salis C; Linden D
Clin Neurophysiol; 2018 Apr; 129(4):815-828. PubMed ID: 29477981
[TBL] [Abstract][Full Text] [Related]
18. Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier.
Al-Salman W; Li Y; Wen P
Neurosci Res; 2021 Nov; 172():26-40. PubMed ID: 33965451
[TBL] [Abstract][Full Text] [Related]
19. A Deep Learning Model for Automated Sleep Stages Classification Using PSG Signals.
Yildirim O; Baloglu UB; Acharya UR
Int J Environ Res Public Health; 2019 Feb; 16(4):. PubMed ID: 30791379
[TBL] [Abstract][Full Text] [Related]
20. Multichannel Sleep Stage Classification and Transfer Learning using Convolutional Neural Networks.
Andreotti F; Phan H; Cooray N; Lo C; Hu MTM; De Vos M
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():171-174. PubMed ID: 30440365
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]