182 related articles for article (PubMed ID: 37529540)
1. LWSleepNet: A lightweight attention-based deep learning model for sleep staging with singlechannel EEG.
Yang C; Li B; Li Y; He Y; Zhang Y
Digit Health; 2023; 9():20552076231188206. PubMed ID: 37529540
[TBL] [Abstract][Full Text] [Related]
2. Automatic sleep staging by a hybrid model based on deep 1D-ResNet-SE and LSTM with single-channel raw EEG signals.
Li W; Gao J
PeerJ Comput Sci; 2023; 9():e1561. PubMed ID: 37810362
[TBL] [Abstract][Full Text] [Related]
3. An End-to-End Multi-Channel Convolutional Bi-LSTM Network for Automatic Sleep Stage Detection.
Toma TI; Choi S
Sensors (Basel); 2023 May; 23(10):. PubMed ID: 37430865
[TBL] [Abstract][Full Text] [Related]
4. InsightSleepNet: the interpretable and uncertainty-aware deep learning network for sleep staging using continuous Photoplethysmography.
Nam B; Bark B; Lee J; Kim IY
BMC Med Inform Decis Mak; 2024 Feb; 24(1):50. PubMed ID: 38355559
[TBL] [Abstract][Full Text] [Related]
5. A Temporal-Spectral Fused and Attention-based Deep Model for Automatic Sleep Staging.
Fu G; Zhou Y; Gong P; Wang P; Shao W; Zhang D
IEEE Trans Neural Syst Rehabil Eng; 2023 Jan; PP():. PubMed ID: 37022069
[TBL] [Abstract][Full Text] [Related]
6. Micro SleepNet: efficient deep learning model for mobile terminal real-time sleep staging.
Liu G; Wei G; Sun S; Mao D; Zhang J; Zhao D; Tian X; Wang X; Chen N
Front Neurosci; 2023; 17():1218072. PubMed ID: 37575302
[TBL] [Abstract][Full Text] [Related]
7. Real-Time Target Detection Method Based on Lightweight Convolutional Neural Network.
Yun J; Jiang D; Liu Y; Sun Y; Tao B; Kong J; Tian J; Tong X; Xu M; Fang Z
Front Bioeng Biotechnol; 2022; 10():861286. PubMed ID: 36051585
[TBL] [Abstract][Full Text] [Related]
8. MRASleepNet: a multi-resolution attention network for sleep stage classification using single-channel EEG.
Yu R; Zhou Z; Wu S; Gao X; Bin G
J Neural Eng; 2022 Dec; 19(6):. PubMed ID: 36379059
[No Abstract] [Full Text] [Related]
9. DenSleepNet: DenseNet based model for sleep staging with two-frequency feature fusion and coordinate attention.
Liu Z; Qin M; Lu Y; Luo S; Zhang Q
Biomed Eng Lett; 2023 Nov; 13(4):751-761. PubMed ID: 37872995
[TBL] [Abstract][Full Text] [Related]
10. A Lightweight Segmented Attention Network for Sleep Staging by Fusing Local Characteristics and Adjacent Information.
Zhou W; Zhu H; Shen N; Chen H; Fu C; Yu H; Shu F; Chen C; Chen W
IEEE Trans Neural Syst Rehabil Eng; 2023; 31():238-247. PubMed ID: 36343008
[TBL] [Abstract][Full Text] [Related]
11. Automatic Sleep Stage Classification Using Temporal Convolutional Neural Network and New Data Augmentation Technique from Raw Single-Channel EEG.
Khalili E; Mohammadzadeh Asl B
Comput Methods Programs Biomed; 2021 Jun; 204():106063. PubMed ID: 33823315
[TBL] [Abstract][Full Text] [Related]
12. Multi-scale ResNet and BiGRU automatic sleep staging based on attention mechanism.
Liu C; Yin Y; Sun Y; Ersoy OK
PLoS One; 2022; 17(6):e0269500. PubMed ID: 35709101
[TBL] [Abstract][Full Text] [Related]
13. Extracting Multi-Scale and Salient Features by MSE Based U-Structure and CBAM for Sleep Staging.
Liu Z; Luo S; Lu Y; Zhang Y; Jiang L; Xiao H
IEEE Trans Neural Syst Rehabil Eng; 2023; 31():31-38. PubMed ID: 36260576
[TBL] [Abstract][Full Text] [Related]
14. Attention based convolutional network for automatic sleep stage classification.
Sun S; Li C; Lv N; Zhang X; Yu Z; Wang H
Biomed Tech (Berl); 2021 Aug; 66(4):335-343. PubMed ID: 33544475
[TBL] [Abstract][Full Text] [Related]
15. A sleep staging model on wavelet-based adaptive spectrogram reconstruction and light weight CNN.
Fei K; Wang J; Pan L; Wang X; Chen B
Comput Biol Med; 2024 May; 173():108300. PubMed ID: 38547654
[TBL] [Abstract][Full Text] [Related]
16. A lightweight automatic sleep staging method for children using single-channel EEG based on edge artificial intelligence.
Zhu L; Wang C; He Z; Zhang Y
World Wide Web; 2022; 25(5):1883-1903. PubMed ID: 35002476
[TBL] [Abstract][Full Text] [Related]
17. An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG.
Eldele E; Chen Z; Liu C; Wu M; Kwoh CK; Li X; Guan C
IEEE Trans Neural Syst Rehabil Eng; 2021; 29():809-818. PubMed ID: 33909566
[TBL] [Abstract][Full Text] [Related]
18. Deep Learning in Automatic Sleep Staging With a Single Channel Electroencephalography.
Fu M; Wang Y; Chen Z; Li J; Xu F; Liu X; Hou F
Front Physiol; 2021; 12():628502. PubMed ID: 33746774
[TBL] [Abstract][Full Text] [Related]
19. MaskSleepNet: A Cross-Modality Adaptation Neural Network for Heterogeneous Signals Processing in Sleep Staging.
Zhu H; Zhou W; Fu C; Wu Y; Shen N; Shu F; Yu H; Chen W; Chen C
IEEE J Biomed Health Inform; 2023 May; 27(5):2353-2364. PubMed ID: 37028323
[TBL] [Abstract][Full Text] [Related]
20. Hybrid manifold-deep convolutional neural network for sleep staging.
Zhang C; Liu S; Han F; Nie Z; Lo B; Zhang Y
Methods; 2022 Jun; 202():164-172. PubMed ID: 33636312
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]