297 related articles for article (PubMed ID: 35898064)
1. Sleep Apnea Detection Using Multi-Error-Reduction Classification System with Multiple Bio-Signals.
Li X; Leung FHF; Su S; Ling SH
Sensors (Basel); 2022 Jul; 22(15):. PubMed ID: 35898064
[TBL] [Abstract][Full Text] [Related]
2. A Hybrid Feature Selection and Extraction Methods for Sleep Apnea Detection Using Bio-Signals.
Li X; Ling SH; Su S
Sensors (Basel); 2020 Aug; 20(15):. PubMed ID: 32756353
[TBL] [Abstract][Full Text] [Related]
3. Feature Selection for the Detection of Sleep Apnea using Multi-Bio Signals from Overnight Polysomnography.
Li X; Al-Ani A; Ling SH
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():1444-1447. PubMed ID: 30440664
[TBL] [Abstract][Full Text] [Related]
4. Assessment of feature selection and classification approaches to enhance information from overnight oximetry in the context of apnea diagnosis.
Alvarez D; Hornero R; Marcos JV; Wessel N; Penzel T; Glos M; Del Campo F
Int J Neural Syst; 2013 Oct; 23(5):1350020. PubMed ID: 23924411
[TBL] [Abstract][Full Text] [Related]
5. Diagnosis of obstructive sleep apnea in children based on the XGBoost algorithm using nocturnal heart rate and blood oxygen feature.
Ye P; Qin H; Zhan X; Wang Z; Liu C; Song B; Kong Y; Jia X; Qi Y; Ji J; Chang L; Ni X; Tai J
Am J Otolaryngol; 2023; 44(2):103714. PubMed ID: 36738700
[TBL] [Abstract][Full Text] [Related]
6. Machine learning-based automatic sleep apnoea and severity level classification using ECG and SpO
Simegn GL; Nemomssa HD; Ayalew MP
J Med Eng Technol; 2022 Feb; 46(2):148-157. PubMed ID: 35060829
[TBL] [Abstract][Full Text] [Related]
7. Obstructive sleep apnea detection using SVM-based classification of ECG signal features.
Almazaydeh L; Elleithy K; Faezipour M
Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():4938-41. PubMed ID: 23367035
[TBL] [Abstract][Full Text] [Related]
8. Performance evaluation of the spectral autocorrelation function and autoregressive models for automated sleep apnea detection using single-lead ECG signal.
Zarei A; Mohammadzadeh Asl B
Comput Methods Programs Biomed; 2020 Oct; 195():105626. PubMed ID: 32634646
[TBL] [Abstract][Full Text] [Related]
9. Application of an optimal class of antisymmetric wavelet filter banks for obstructive sleep apnea diagnosis using ECG signals.
Sharma M; Agarwal S; Acharya UR
Comput Biol Med; 2018 Sep; 100():100-113. PubMed ID: 29990643
[TBL] [Abstract][Full Text] [Related]
10. Deep learning of sleep apnea-hypopnea events for accurate classification of obstructive sleep apnea and determination of clinical severity.
Yook S; Kim D; Gupte C; Joo EY; Kim H
Sleep Med; 2024 Feb; 114():211-219. PubMed ID: 38232604
[TBL] [Abstract][Full Text] [Related]
11. Investigating the contribution of distance-based features to automatic sleep stage classification.
Gharbali AA; Najdi S; Fonseca JM
Comput Biol Med; 2018 May; 96():8-23. PubMed ID: 29529528
[TBL] [Abstract][Full Text] [Related]
12. A model for obstructive sleep apnea detection using a multi-layer feed-forward neural network based on electrocardiogram, pulse oxygen saturation, and body mass index.
Li Z; Li Y; Zhao G; Zhang X; Xu W; Han D
Sleep Breath; 2021 Dec; 25(4):2065-2072. PubMed ID: 33754247
[TBL] [Abstract][Full Text] [Related]
13. Classification of Sleep Apnea Severity by Electrocardiogram Monitoring Using a Novel Wearable Device.
Baty F; Boesch M; Widmer S; Annaheim S; Fontana P; Camenzind M; Rossi RM; Schoch OD; Brutsche MH
Sensors (Basel); 2020 Jan; 20(1):. PubMed ID: 31947905
[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. Automated detection of obstructive sleep apnea in more than 8000 subjects using frequency optimized orthogonal wavelet filter bank with respiratory and oximetry signals.
Sharma M; Kumbhani D; Tiwari J; Kumar TS; Acharya UR
Comput Biol Med; 2022 May; 144():105364. PubMed ID: 35299046
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Sleep-wake stage detection with single channel ECG and hybrid machine learning model in patients with obstructive sleep apnea.
Bozkurt F; Uçar MK; Bilgin C; Zengin A
Phys Eng Sci Med; 2021 Mar; 44(1):63-77. PubMed ID: 33398636
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Automatic identification of respiratory events based on nasal airflow and respiratory effort of the chest and abdomen.
Liu J; Li Q; Chen Y; Wang B; Li Y; Xin Y
Physiol Meas; 2021 Jul; 42(7):. PubMed ID: 33887711
[No Abstract] [Full Text] [Related]
20. Detection of k-complexes in EEG signals using a multi-domain feature extraction coupled with a least square support vector machine classifier.
Al-Salman W; Li Y; Wen P
Neurosci Res; 2021 Nov; 172():26-40. PubMed ID: 33965451
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]