189 related articles for article (PubMed ID: 23627659)
41. 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]
42. Decision System Integrating Preferences to Support Sleep Staging.
Ugon A; Sedki K; Kotti A; Seroussi B; Philippe C; Ganascia JG; Garda P; Bouaud J; Pinna A
Stud Health Technol Inform; 2016; 228():514-8. PubMed ID: 27577436
[TBL] [Abstract][Full Text] [Related]
43. An automatic single-channel EEG-based sleep stage scoring method based on hidden Markov Model.
Ghimatgar H; Kazemi K; Helfroush MS; Aarabi A
J Neurosci Methods; 2019 Aug; 324():108320. PubMed ID: 31228517
[TBL] [Abstract][Full Text] [Related]
44. 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]
45. Nonlinear Dynamics Measures for Automated EEG-Based Sleep Stage Detection.
Acharya UR; Bhat S; Faust O; Adeli H; Chua EC; Lim WJ; Koh JE
Eur Neurol; 2015; 74(5-6):268-87. PubMed ID: 26650683
[TBL] [Abstract][Full Text] [Related]
46. A Distributed Classification Procedure for Automatic Sleep Stage Scoring Based on Instantaneous Electroencephalogram Phase and Envelope Features.
Karimzadeh F; Boostani R; Seraj E; Sameni R
IEEE Trans Neural Syst Rehabil Eng; 2018 Feb; 26(2):362-370. PubMed ID: 29432107
[TBL] [Abstract][Full Text] [Related]
47. Deep Learning and Insomnia: Assisting Clinicians With Their Diagnosis.
Shahin M; Ahmed B; Hamida ST; Mulaffer FL; Glos M; Penzel T
IEEE J Biomed Health Inform; 2017 Nov; 21(6):1546-1553. PubMed ID: 28092583
[TBL] [Abstract][Full Text] [Related]
48. A rule-based automatic sleep staging method.
Liang SF; Kuo CE; Hu YH; Cheng YS
J Neurosci Methods; 2012 Mar; 205(1):169-76. PubMed ID: 22245090
[TBL] [Abstract][Full Text] [Related]
49. Designing a robust feature extraction method based on optimum allocation and principal component analysis for epileptic EEG signal classification.
Siuly S; Li Y
Comput Methods Programs Biomed; 2015 Apr; 119(1):29-42. PubMed ID: 25704869
[TBL] [Abstract][Full Text] [Related]
50. [A study of sleep stage classification based on permutation entropy for electroencephalogram].
Li G; Fan Y; Pang Q
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2009 Aug; 26(4):869-72. PubMed ID: 19813629
[TBL] [Abstract][Full Text] [Related]
51. Measuring dissimilarity between respiratory effort signals based on uniform scaling for sleep staging.
Long X; Yang J; Weysen T; Haakma R; Foussier J; Fonseca P; Aarts RM
Physiol Meas; 2014 Dec; 35(12):2529-42. PubMed ID: 25407770
[TBL] [Abstract][Full Text] [Related]
52. Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.
Najdi S; Gharbali AA; Fonseca JM
Biomed Eng Online; 2017 Aug; 16(Suppl 1):78. PubMed ID: 28830438
[TBL] [Abstract][Full Text] [Related]
53. Quaternion Singular Spectrum Analysis of Electroencephalogram With Application in Sleep Analysis.
Enshaeifar S; Kouchaki S; Took CC; Sanei S
IEEE Trans Neural Syst Rehabil Eng; 2016 Jan; 24(1):57-67. PubMed ID: 26276995
[TBL] [Abstract][Full Text] [Related]
54. Cascaded LSTM recurrent neural network for automated sleep stage classification using single-channel EEG signals.
Michielli N; Acharya UR; Molinari F
Comput Biol Med; 2019 Mar; 106():71-81. PubMed ID: 30685634
[TBL] [Abstract][Full Text] [Related]
55. A Multi-Level Interpretable Sleep Stage Scoring System by Infusing Experts' Knowledge Into a Deep Network Architecture.
Niknazar H; Mednick SC
IEEE Trans Pattern Anal Mach Intell; 2024 Jul; 46(7):5044-5061. PubMed ID: 38358869
[TBL] [Abstract][Full Text] [Related]
56. 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]
57. 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]
58. Self-evaluated automatic classifier as a decision-support tool for sleep/wake staging.
Charbonnier S; Zoubek L; Lesecq S; Chapotot F
Comput Biol Med; 2011 Jun; 41(6):380-9. PubMed ID: 21497802
[TBL] [Abstract][Full Text] [Related]
59. Quantum neural network-based EEG filtering for a brain-computer interface.
Gandhi V; Prasad G; Coyle D; Behera L; McGinnity TM
IEEE Trans Neural Netw Learn Syst; 2014 Feb; 25(2):278-88. PubMed ID: 24807028
[TBL] [Abstract][Full Text] [Related]
60. Ensemble learning algorithm based on multi-parameters for sleep staging.
Wang Q; Zhao D; Wang Y; Hou X
Med Biol Eng Comput; 2019 Aug; 57(8):1693-1707. PubMed ID: 31104274
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
