144 related articles for article (PubMed ID: 38063156)
21. Novel and noninvasive methods for in-home sleep measurement and subsequent state coding in 12-month-old infants.
Horger MN
Infant Behav Dev; 2022 Nov; 69():101775. PubMed ID: 36126380
[TBL] [Abstract][Full Text] [Related]
22. Development of a human-computer collaborative sleep scoring system for polysomnography recordings.
Liang SF; Shih YH; Chen PY; Kuo CE
PLoS One; 2019; 14(7):e0218948. PubMed ID: 31291270
[TBL] [Abstract][Full Text] [Related]
23. Automatic identification of sleep and wakefulness using single-channel EEG and respiratory polygraphy signals for the diagnosis of obstructive sleep apnea.
Sabil A; Vanbuis J; Baffet G; Feuilloy M; Le Vaillant M; Meslier N; Gagnadoux F
J Sleep Res; 2019 Apr; 28(2):e12795. PubMed ID: 30478923
[TBL] [Abstract][Full Text] [Related]
24. Automatic sleep staging using state machine-controlled decision trees.
Imtiaz SA; Rodriguez-Villegas E
Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():378-81. PubMed ID: 26736278
[TBL] [Abstract][Full Text] [Related]
25. The Virtual Sleep Lab-A Novel Method for Accurate Four-Class Sleep Staging Using Heart-Rate Variability from Low-Cost Wearables.
Topalidis P; Heib DPJ; Baron S; Eigl ES; Hinterberger A; Schabus M
Sensors (Basel); 2023 Feb; 23(5):. PubMed ID: 36904595
[TBL] [Abstract][Full Text] [Related]
26. A sleep stage estimation algorithm based on cardiorespiratory signals derived from a suprasternal pressure sensor.
Cerina L; Overeem S; Papini GB; van Dijk JP; Vullings R; van Meulen F; Ross M; Cerny A; Anderer P; Fonseca P
J Sleep Res; 2024 Apr; 33(2):e14015. PubMed ID: 37572052
[TBL] [Abstract][Full Text] [Related]
27. Long Short-Term Memory Networks for Unconstrained Sleep Stage Classification Using Polyvinylidene Fluoride Film Sensor.
Choi SH; Kwon HB; Jin HW; Yoon H; Lee MH; Lee YJ; Park KS
IEEE J Biomed Health Inform; 2020 Dec; 24(12):3606-3615. PubMed ID: 32149661
[TBL] [Abstract][Full Text] [Related]
28. Accurate Deep Learning-Based Sleep Staging in a Clinical Population With Suspected Obstructive Sleep Apnea.
Korkalainen H; Aakko J; Nikkonen S; Kainulainen S; Leino A; Duce B; Afara IO; Myllymaa S; Toyras J; Leppanen T
IEEE J Biomed Health Inform; 2020 Jul; 24(7):2073-2081. PubMed ID: 31869808
[TBL] [Abstract][Full Text] [Related]
29. 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]
30. Performance of Somno-Art Software compared to polysomnography interscorer variability: A multi-center study.
Thiesse L; Staner L; Fuchs G; Kirscher D; Dehouck V; Roth T; Schaffhauser JY; Saoud JB; Viola AU
Sleep Med; 2022 Aug; 96():14-19. PubMed ID: 35576829
[TBL] [Abstract][Full Text] [Related]
31. Automatic scoring of sleep stages and cortical arousals using two electrodes on the forehead: validation in healthy adults.
Popovic D; Khoo M; Westbrook P
J Sleep Res; 2014 Apr; 23(2):211-21. PubMed ID: 24313630
[TBL] [Abstract][Full Text] [Related]
32. Expert-level sleep scoring with deep neural networks.
Biswal S; Sun H; Goparaju B; Westover MB; Sun J; Bianchi MT
J Am Med Inform Assoc; 2018 Dec; 25(12):1643-1650. PubMed ID: 30445569
[TBL] [Abstract][Full Text] [Related]
33. Sleep stage classification with ECG and respiratory effort.
Fonseca P; Long X; Radha M; Haakma R; Aarts RM; Rolink J
Physiol Meas; 2015 Oct; 36(10):2027-40. PubMed ID: 26289580
[TBL] [Abstract][Full Text] [Related]
34. An algorithm for actigraphy-based sleep/wake scoring: Comparison with polysomnography.
Lüdtke S; Hermann W; Kirste T; Beneš H; Teipel S
Clin Neurophysiol; 2021 Jan; 132(1):137-145. PubMed ID: 33278666
[TBL] [Abstract][Full Text] [Related]
35. Polysomnography scoring-related training and quantitative assessment for improving interscorer agreement.
Liao YS; Wu MC; Li CX; Lin WK; Lin CY; Liang SF
J Clin Sleep Med; 2024 Feb; 20(2):271-278. PubMed ID: 37811900
[TBL] [Abstract][Full Text] [Related]
36. IntelliSleepScorer, a software package with a graphic user interface for automated sleep stage scoring in mice based on a light gradient boosting machine algorithm.
Wang LA; Kern R; Yu E; Choi S; Pan JQ
Sci Rep; 2023 Mar; 13(1):4275. PubMed ID: 36922536
[TBL] [Abstract][Full Text] [Related]
37. Recommendations for performance assessment of automatic sleep staging algorithms.
Imtiaz SA; Rodriguez-Villegas E
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():5044-7. PubMed ID: 25571126
[TBL] [Abstract][Full Text] [Related]
38. Detection of Nocturnal Slow Wave Sleep Based on Cardiorespiratory Activity in Healthy Adults.
Long X; Fonseca P; Aarts RM; Haakma R; Rolink J; Leonhardt S
IEEE J Biomed Health Inform; 2017 Jan; 21(1):123-133. PubMed ID: 26452293
[TBL] [Abstract][Full Text] [Related]
39. [The concordance of manuel (visual) scoring and automatic analysis in sleep staging].
Oztürk O; Mutlu LC; Sağcan G; Deniz Y; Cuhadaroğlu C
Tuberk Toraks; 2009; 57(3):306-13. PubMed ID: 19787470
[TBL] [Abstract][Full Text] [Related]
40.
; ; . PubMed ID:
[No Abstract] [Full Text] [Related]
[Previous] [Next] [New Search]