240 related articles for article (PubMed ID: 21096343)
1. An automatic detector of drowsiness based on spectral analysis and wavelet decomposition of EEG records.
Garces Correa A; Laciar Leber E
Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():1405-8. PubMed ID: 21096343
[TBL] [Abstract][Full Text] [Related]
2. Bayesian Nonnegative CP Decomposition-Based Feature Extraction Algorithm for Drowsiness Detection.
Qian D; Wang B; Qing X; Zhang T; Zhang Y; Wang X; Nakamura M
IEEE Trans Neural Syst Rehabil Eng; 2017 Aug; 25(8):1297-1308. PubMed ID: 27775525
[TBL] [Abstract][Full Text] [Related]
3. Automatic detection of drowsiness in EEG records based on multimodal analysis.
Garcés Correa A; Orosco L; Laciar E
Med Eng Phys; 2014 Feb; 36(2):244-9. PubMed ID: 23972332
[TBL] [Abstract][Full Text] [Related]
4. Validation of a novel automatic sleep spindle detector with high performance during sleep in middle aged subjects.
Wendt SL; Christensen JA; Kempfner J; Leonthin HL; Jennum P; Sorensen HB
Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():4250-3. PubMed ID: 23366866
[TBL] [Abstract][Full Text] [Related]
5. Automatic sleep stage classification based on EEG signals by using neural networks and wavelet packet coefficients.
Ebrahimi F; Mikaeili M; Estrada E; Nazeran H
Annu Int Conf IEEE Eng Med Biol Soc; 2008; 2008():1151-4. PubMed ID: 19162868
[TBL] [Abstract][Full Text] [Related]
6. An efficient automatic arousals detection algorithm in single channel EEG.
Ugur TK; Erdamar A
Comput Methods Programs Biomed; 2019 May; 173():131-138. PubMed ID: 31046987
[TBL] [Abstract][Full Text] [Related]
7. An improved algorithm for the automatic detection and characterization of slow eye movements.
Cona F; Pizza F; Provini F; Magosso E
Med Eng Phys; 2014 Jul; 36(7):954-61. PubMed ID: 24768562
[TBL] [Abstract][Full Text] [Related]
8. Micro- and macrostructure of sleep EEG.
Malinowska U; Durka PJ; Blinowska KJ; Szelenberger W; Wakarow A
IEEE Eng Med Biol Mag; 2006; 25(4):26-31. PubMed ID: 16898655
[No Abstract] [Full Text] [Related]
9. A decision support system for automatic sleep staging from EEG signals using tunable Q-factor wavelet transform and spectral features.
Hassan AR; Bhuiyan MI
J Neurosci Methods; 2016 Sep; 271():107-18. PubMed ID: 27456762
[TBL] [Abstract][Full Text] [Related]
10. A novel wavelet-based index to detect epileptic seizures using scalp EEG signals.
Zandi AS; Dumont GA; Javidan M; Tafreshi R; MacLeod BA; Ries CR; Puil E
Annu Int Conf IEEE Eng Med Biol Soc; 2008; 2008():919-22. PubMed ID: 19162807
[TBL] [Abstract][Full Text] [Related]
11. Drowsiness Detection by Bayesian-Copula Discriminant Classifier Based on EEG Signals During Daytime Short Nap.
Qian D; Wang B; Qing X; Zhang T; Zhang Y; Wang X; Nakamura M
IEEE Trans Biomed Eng; 2017 Apr; 64(4):743-754. PubMed ID: 27254855
[TBL] [Abstract][Full Text] [Related]
12. Automatic classification methods for detecting drowsiness using wavelet packet transform extracted time-domain features from single-channel EEG signal.
B VP; Chinara S
J Neurosci Methods; 2021 Jan; 347():108927. PubMed ID: 32941920
[TBL] [Abstract][Full Text] [Related]
13. An algorithm for automatic detection of drowsiness for use in wearable EEG systems.
Patrick KC; Imtiaz SA; Bowyer S; Rodriguez-Villegas E
Annu Int Conf IEEE Eng Med Biol Soc; 2016 Aug; 2016():3523-3526. PubMed ID: 28269058
[TBL] [Abstract][Full Text] [Related]
14. Generalizability of Frequency Weighting Curve for Extraction of Spectral Drowsy Component From the EEG Signals Recorded in Eyes-Closed Condition.
Putilov AA; Donskaya OG; Verevkin EG
Clin EEG Neurosci; 2017 Jul; 48(4):259-269. PubMed ID: 27733638
[TBL] [Abstract][Full Text] [Related]
15. Automated Sleep Stages Classification Using Convolutional Neural Network From Raw and Time-Frequency Electroencephalogram Signals: Systematic Evaluation Study.
Haghayegh S; Hu K; Stone K; Redline S; Schernhammer E
J Med Internet Res; 2023 Feb; 25():e40211. PubMed ID: 36763454
[TBL] [Abstract][Full Text] [Related]
16. Classification of sleep stages in infants: a neuro fuzzy approach.
Heiss JE; Held CM; Estévez PA; Perez CA; Holzmann CA; Pérez JP
IEEE Eng Med Biol Mag; 2002; 21(5):147-51. PubMed ID: 12405069
[No Abstract] [Full Text] [Related]
17. Epileptic EEG Identification via LBP Operators on Wavelet Coefficients.
Yuan Q; Zhou W; Xu F; Leng Y; Wei D
Int J Neural Syst; 2018 Oct; 28(8):1850010. PubMed ID: 29665725
[TBL] [Abstract][Full Text] [Related]
18. A Multivariate Approach for Patient-Specific EEG Seizure Detection Using Empirical Wavelet Transform.
Bhattacharyya A; Pachori RB
IEEE Trans Biomed Eng; 2017 Sep; 64(9):2003-2015. PubMed ID: 28092514
[TBL] [Abstract][Full Text] [Related]
19. Modeling the time-varying microstructure of simulated sleep EEG spindles using time-frequency analysis methods.
Xanthopoulos P; Golemati S; Sakkalis V; Ktonas PY; Zervakis M; Soldatos CR
Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():2438-41. PubMed ID: 17945715
[TBL] [Abstract][Full Text] [Related]
20. Automatic sleep staging using empirical mode decomposition, discrete wavelet transform, time-domain, and nonlinear dynamics features of heart rate variability signals.
Ebrahimi F; Setarehdan SK; Ayala-Moyeda J; Nazeran H
Comput Methods Programs Biomed; 2013 Oct; 112(1):47-57. PubMed ID: 23895941
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
