162 related articles for article (PubMed ID: 35853400)
21. Sleep staging algorithm based on multichannel data adding and multifeature screening.
Huang W; Guo B; Shen Y; Tang X; Zhang T; Li D; Jiang Z
Comput Methods Programs Biomed; 2020 Apr; 187():105253. PubMed ID: 31812884
[TBL] [Abstract][Full Text] [Related]
22. Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease.
Christensen JA; Zoetmulder M; Koch H; Frandsen R; Arvastson L; Christensen SR; Jennum P; Sorensen HB
J Neurosci Methods; 2014 Sep; 235():262-76. PubMed ID: 25088694
[TBL] [Abstract][Full Text] [Related]
23. Assessment of Itakura Distance as a valuable feature for computer-aided classification of sleep stages.
Ebrahimi F; Mikaili M; Estrada E; Nazeran H
Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():3300-3. PubMed ID: 18002701
[TBL] [Abstract][Full Text] [Related]
24. An accurate sleep stages classification system using a new class of optimally time-frequency localized three-band wavelet filter bank.
Sharma M; Goyal D; Achuth PV; Acharya UR
Comput Biol Med; 2018 Jul; 98():58-75. PubMed ID: 29775912
[TBL] [Abstract][Full Text] [Related]
25. Wavelet analysis of electroencephalographic and electro-oculographic changes during the sleep onset period.
Magosso E; Ursino M; Provini F; Montagna P
Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():4006-10. PubMed ID: 18002878
[TBL] [Abstract][Full Text] [Related]
26. Orthogonal convolutional neural networks for automatic sleep stage classification based on single-channel EEG.
Zhang J; Yao R; Ge W; Gao J
Comput Methods Programs Biomed; 2020 Jan; 183():105089. PubMed ID: 31586788
[TBL] [Abstract][Full Text] [Related]
27. Jumping Knowledge Based Spatial-Temporal Graph Convolutional Networks for Automatic Sleep Stage Classification.
Ji X; Li Y; Wen P
IEEE Trans Neural Syst Rehabil Eng; 2022; 30():1464-1472. PubMed ID: 35584068
[TBL] [Abstract][Full Text] [Related]
28. Research on removal algorithm of EOG artifacts in single-channel EEG signals based on CEEMDAN-BD.
Wu Q; Zhang W; Wang Y; Zhang W; Liu X
Comput Methods Biomech Biomed Engin; 2021 Sep; 24(12):1368-1379. PubMed ID: 33620279
[TBL] [Abstract][Full Text] [Related]
29. A Deep Learning Architecture for Temporal Sleep Stage Classification Using Multivariate and Multimodal Time Series.
Chambon S; Galtier MN; Arnal PJ; Wainrib G; Gramfort A
IEEE Trans Neural Syst Rehabil Eng; 2018 Apr; 26(4):758-769. PubMed ID: 29641380
[TBL] [Abstract][Full Text] [Related]
30. MVF-SleepNet: Multi-View Fusion Network for Sleep Stage Classification.
Li Y; Chen J; Ma W; Zhao G; Fan X
IEEE J Biomed Health Inform; 2024 May; 28(5):2485-2495. PubMed ID: 36129857
[TBL] [Abstract][Full Text] [Related]
31. Efficient sleep classification based on entropy features and a support vector machine classifier.
Zhang Z; Wei S; Zhu G; Liu F; Li Y; Dong X; Liu C; Liu F
Physiol Meas; 2018 Nov; 39(11):115005. PubMed ID: 30475743
[TBL] [Abstract][Full Text] [Related]
32. Sleep staging classification based on a new parallel fusion method of multiple sources signals.
Hei Y; Yuan T; Fan Z; Yang B; Hu J
Physiol Meas; 2022 Apr; 43(4):. PubMed ID: 35381584
[No Abstract] [Full Text] [Related]
33. Deep learning for healthcare applications based on physiological signals: A review.
Faust O; Hagiwara Y; Hong TJ; Lih OS; Acharya UR
Comput Methods Programs Biomed; 2018 Jul; 161():1-13. PubMed ID: 29852952
[TBL] [Abstract][Full Text] [Related]
34. Proof of concept: Screening for REM sleep behaviour disorder with a minimal set of sensors.
Cooray N; Andreotti F; Lo C; Symmonds M; Hu MTM; De Vos M
Clin Neurophysiol; 2021 Apr; 132(4):904-913. PubMed ID: 33636605
[TBL] [Abstract][Full Text] [Related]
35. EEG Sleep Stages Classification Based on Time Domain Features and Structural Graph Similarity.
Diykh M; Li Y; Wen P
IEEE Trans Neural Syst Rehabil Eng; 2016 Nov; 24(11):1159-1168. PubMed ID: 27101613
[TBL] [Abstract][Full Text] [Related]
36. MixSleepNet: A Multi-Type Convolution Combined Sleep Stage Classification Model.
Ji X; Li Y; Wen P; Barua P; Acharya UR
Comput Methods Programs Biomed; 2024 Feb; 244():107992. PubMed ID: 38218118
[TBL] [Abstract][Full Text] [Related]
37. Multiple classifier systems for automatic sleep scoring in mice.
Gao V; Turek F; Vitaterna M
J Neurosci Methods; 2016 May; 264():33-39. PubMed ID: 26928255
[TBL] [Abstract][Full Text] [Related]
38. Assessment of the suitability of using a forehead EEG electrode set and chin EMG electrodes for sleep staging in polysomnography.
Myllymaa S; Muraja-Murro A; Westeren-Punnonen S; Hukkanen T; Lappalainen R; Mervaala E; Töyräs J; Sipilä K; Myllymaa K
J Sleep Res; 2016 Dec; 25(6):636-645. PubMed ID: 27230805
[TBL] [Abstract][Full Text] [Related]
39. Effects of amphetamine, diazepam and caffeine on polysomnography (EEG, EMG, EOG)-derived variables measured using telemetry in Cynomolgus monkeys.
Authier S; Bassett L; Pouliot M; Rachalski A; Troncy E; Paquette D; Mongrain V
J Pharmacol Toxicol Methods; 2014; 70(1):86-93. PubMed ID: 24878255
[TBL] [Abstract][Full Text] [Related]
40. Automated identification of sleep disorders using wavelet-based features extracted from electrooculogram and electromyogram signals.
Sharma M; Darji J; Thakrar M; Acharya UR
Comput Biol Med; 2022 Apr; 143():105224. PubMed ID: 35091364
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
