These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

114 related articles for article (PubMed ID: 35060814)

  • 1. An automated method for sleep apnoea detection using HRV.
    Karimi Moridani M
    J Med Eng Technol; 2022 Feb; 46(2):158-173. PubMed ID: 35060814
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Comparing Different Methods of Hand-crafted HRV, EDR and CPC Features for Sleep Apnoea Detection.
    Sadr N; Chazal P
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():3870-3873. PubMed ID: 31946718
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Systematic comparison of different algorithms for apnoea detection based on electrocardiogram recordings.
    Penzel T; McNames J; Murray A; de Chazal P; Moody G; Raymond B
    Med Biol Eng Comput; 2002 Jul; 40(4):402-7. PubMed ID: 12227626
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Non-invasive Diagnosis of Sleep Apnoea Using ECG and Respiratory Bands.
    Sadr N; de Chazal P
    Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():1609-1612. PubMed ID: 31946204
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Sleep apnoea classification using heart rate variability, ECG derived respiration and cardiopulmonary coupling parameters.
    de Chazal P; Sadr N
    Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():3203-3206. PubMed ID: 28268989
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Cross-correlation of EEG frequency bands and heart rate variability for sleep apnoea classification.
    Abdullah H; Maddage NC; Cosic I; Cvetkovic D
    Med Biol Eng Comput; 2010 Dec; 48(12):1261-9. PubMed ID: 21046273
    [TBL] [Abstract][Full Text] [Related]  

  • 7. An ECG oximetry system for identifying obstructive and central apnoea events.
    de Chazal P; Sadr N; Jayawardhana M
    Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():7671-4. PubMed ID: 26738069
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Apnoea detection using ECG signal based on machine learning classifiers and its performances.
    J RG; K D
    J Med Eng Technol; 2023 Oct; 47(7):344-354. PubMed ID: 38625408
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Automated recognition of patients with obstructive sleep apnoea using wavelet-based features of electrocardiogram recordings.
    Khandoker AH; Karmakar CK; Palaniswami M
    Comput Biol Med; 2009 Jan; 39(1):88-96. PubMed ID: 19144328
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Sleep apnoea diagnosis using respiratory effort-based signals - a comparative study.
    Sadr N; Jayawardhana M; de Chazal P
    Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():1551-1554. PubMed ID: 29060176
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Sleep apnoea episodes recognition by a committee of ELM classifiers from ECG signal.
    Sadr N; de Chazal P; van Schaik A; Breen P
    Annu Int Conf IEEE Eng Med Biol Soc; 2015; 2015():7675-8. PubMed ID: 26738070
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea.
    de Chazal P; Heneghan C; Sheridan E; Reilly R; Nolan P; O'Malley M
    IEEE Trans Biomed Eng; 2003 Jun; 50(6):686-96. PubMed ID: 12814235
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Multimodal detection of sleep apnoea using electrocardiogram and oximetry signals.
    de Chazal P; Heneghan C; McNicholas WT
    Philos Trans A Math Phys Eng Sci; 2009 Jan; 367(1887):369-89. PubMed ID: 18974035
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Automatic screening of obstructive sleep apnea from the ECG based on empirical mode decomposition and wavelet analysis.
    Mendez MO; Corthout J; Van Huffel S; Matteucci M; Penzel T; Cerutti S; Bianchi AM
    Physiol Meas; 2010 Mar; 31(3):273-89. PubMed ID: 20086277
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Detection of sleep apnea from surface ECG based on features extracted by an autoregressive model.
    Mendez MO; Ruini DD; Villantieri OP; Matteucci M; Penzel T; Cerutti S; Bianchi AM
    Annu Int Conf IEEE Eng Med Biol Soc; 2007; 2007():6106-9. PubMed ID: 18003408
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automated detection of sleep apnea using sparse residual entropy features with various dictionaries extracted from heart rate and EDR signals.
    Viswabhargav CSS; Tripathy RK; Acharya UR
    Comput Biol Med; 2019 May; 108():20-30. PubMed ID: 31003176
    [TBL] [Abstract][Full Text] [Related]  

  • 17. [An algorithm based on ECG signal for sleep apnea syndrome detection].
    Yu X; Tu Y; Huang C; Ye S; Chen H
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2013 Oct; 30(5):999-1002. PubMed ID: 24459959
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Differentiating obstructive from central and complex sleep apnea using an automated electrocardiogram-based method.
    Thomas RJ; Mietus JE; Peng CK; Gilmartin G; Daly RW; Goldberger AL; Gottlieb DJ
    Sleep; 2007 Dec; 30(12):1756-69. PubMed ID: 18246985
    [TBL] [Abstract][Full Text] [Related]  

  • 19. An algorithm for sleep apnea detection from single-lead ECG using Hermite basis functions.
    Sharma H; Sharma KK
    Comput Biol Med; 2016 Oct; 77():116-24. PubMed ID: 27543782
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automated sleep apnea detection from cardio-pulmonary signal using bivariate fast and adaptive EMD coupled with cross time-frequency analysis.
    Tripathy RK; Gajbhiye P; Acharya UR
    Comput Biol Med; 2020 May; 120():103769. PubMed ID: 32421659
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.