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.
148 related articles for article (PubMed ID: 39029435)
1. Automatic detection of sleep apnea from a single-lead ECG signal based on spiking neural network model. Tyagi PK; Agrawal D Comput Biol Med; 2024 Sep; 179():108877. PubMed ID: 39029435 [TBL] [Abstract][Full Text] [Related]
2. A Sleep Apnea Detection System Based on a One-Dimensional Deep Convolution Neural Network Model Using Single-Lead Electrocardiogram. Chang HY; Yeh CY; Lee CT; Lin CC Sensors (Basel); 2020 Jul; 20(15):. PubMed ID: 32722630 [TBL] [Abstract][Full Text] [Related]
3. A RR interval based automated apnea detection approach using residual network. Wang L; Lin Y; Wang J Comput Methods Programs Biomed; 2019 Jul; 176():93-104. PubMed ID: 31200916 [TBL] [Abstract][Full Text] [Related]
4. MPCNN: A Novel Matrix Profile Approach for CNN-based Single Lead Sleep Apnea in Classification Problem. Nguyen HX; Nguyen DV; Pham HH; Do CD IEEE J Biomed Health Inform; 2024 Aug; 28(8):4878-4890. PubMed ID: 38713565 [TBL] [Abstract][Full Text] [Related]
5. Sleep apnea detection from single-lead electrocardiogram signals using effective deep-shallow fusion network. Li P; Ma W; Yue H; Lei W; Fan X; Li Y Physiol Meas; 2024 Feb; 45(2):. PubMed ID: 38237197 [No Abstract] [Full Text] [Related]
6. Sleep apnea detection from ECG using variational mode decomposition. Sharma H; Sharma KK Biomed Phys Eng Express; 2020 Jan; 6(1):015026. PubMed ID: 33438614 [TBL] [Abstract][Full Text] [Related]
7. A Deep Learning Framework for Automatic Sleep Apnea Classification Based on Empirical Mode Decomposition Derived from Single-Lead Electrocardiogram. Setiawan F; Lin CW Life (Basel); 2022 Sep; 12(10):. PubMed ID: 36294943 [TBL] [Abstract][Full Text] [Related]
8. Detection of Sleep Apnea from Single-Lead ECG Signal Using a Time Window Artificial Neural Network. Wang T; Lu C; Shen G Biomed Res Int; 2019; 2019():9768072. PubMed ID: 31950061 [TBL] [Abstract][Full Text] [Related]
9. 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]
10. EfficientNet-based machine learning architecture for sleep apnea identification in clinical single-lead ECG signal data sets. Liu MH; Chien SY; Wu YL; Sun TH; Huang CS; Hsu KC; Hang LW Biomed Eng Online; 2024 Jun; 23(1):57. PubMed ID: 38902671 [TBL] [Abstract][Full Text] [Related]
11. Contribution of Different Subbands of ECG in Sleep Apnea Detection Evaluated Using Filter Bank Decomposition and a Convolutional Neural Network. Yeh CY; Chang HY; Hu JY; Lin CC Sensors (Basel); 2022 Jan; 22(2):. PubMed ID: 35062470 [TBL] [Abstract][Full Text] [Related]
12. SCNN: Scalogram-based convolutional neural network to detect obstructive sleep apnea using single-lead electrocardiogram signals. Mashrur FR; Islam MS; Saha DK; Islam SMR; Moni MA Comput Biol Med; 2021 Jul; 134():104532. PubMed ID: 34102402 [TBL] [Abstract][Full Text] [Related]
13. [Sleep apnea automatic detection method based on convolutional neural network]. Gao Q; Shang L; Wu K Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2021 Aug; 38(4):678-685. PubMed ID: 34459167 [TBL] [Abstract][Full Text] [Related]
14. 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]
15. [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]
16. Deep Learning Forecasts the Occurrence of Sleep Apnea from Single-Lead ECG. Bahrami M; Forouzanfar M Cardiovasc Eng Technol; 2022 Dec; 13(6):809-815. PubMed ID: 35301676 [TBL] [Abstract][Full Text] [Related]
17. Heart rate variability feature selection in the presence of sleep apnea: An expert system for the characterization and detection of the disorder. Martín-González S; Navarro-Mesa JL; Juliá-Serdá G; Kraemer JF; Wessel N; Ravelo-García AG Comput Biol Med; 2017 Dec; 91():47-58. PubMed ID: 29040884 [TBL] [Abstract][Full Text] [Related]
18. 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]
19. Deep learning in the cross-time frequency domain for sleep staging from a single-lead electrocardiogram. Li Q; Li Q; Liu C; Shashikumar SP; Nemati S; Clifford GD Physiol Meas; 2018 Dec; 39(12):124005. PubMed ID: 30524025 [TBL] [Abstract][Full Text] [Related]
20. A method to detect sleep apnea using residual attention mechanism network from single-lead ECG signal. Wang T; Lu C; Sun Y; Fang H; Jiang W; Liu C Biomed Tech (Berl); 2022 Oct; 67(5):357-365. PubMed ID: 35920638 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]