223 related articles for article (PubMed ID: 26283943)
1. Sleep spindle and K-complex detection using tunable Q-factor wavelet transform and morphological component analysis.
Lajnef T; Chaibi S; Eichenlaub JB; Ruby PM; Aguera PE; Samet M; Kachouri A; Jerbi K
Front Hum Neurosci; 2015; 9():414. PubMed ID: 26283943
[TBL] [Abstract][Full Text] [Related]
2. Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS).
Lajnef T; O'Reilly C; Combrisson E; Chaibi S; Eichenlaub JB; Ruby PM; Aguera PE; Samet M; Kachouri A; Frenette S; Carrier J; Jerbi K
Front Neuroinform; 2017; 11():15. PubMed ID: 28303099
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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]
5. A reliable approach to distinguish between transient with and without HFOs using TQWT and MCA.
Chaibi S; Lajnef T; Sakka Z; Samet M; Kachouri A
J Neurosci Methods; 2014 Jul; 232():36-46. PubMed ID: 24814526
[TBL] [Abstract][Full Text] [Related]
6. Detection of K-complexes and sleep spindles (DETOKS) using sparse optimization.
Parekh A; Selesnick IW; Rapoport DM; Ayappa I
J Neurosci Methods; 2015 Aug; 251():37-46. PubMed ID: 25956566
[TBL] [Abstract][Full Text] [Related]
7. Epileptic seizure detection in EEG signals using tunable-Q factor wavelet transform and bootstrap aggregating.
Hassan AR; Siuly S; Zhang Y
Comput Methods Programs Biomed; 2016 Dec; 137():247-259. PubMed ID: 28110729
[TBL] [Abstract][Full Text] [Related]
8. A RUSBoosted tree method for k-complex detection using tunable Q-factor wavelet transform and multi-domain feature extraction.
Li Y; Dong X
Front Neurosci; 2023; 17():1108059. PubMed ID: 36998730
[TBL] [Abstract][Full Text] [Related]
9. A feature extraction technique based on tunable Q-factor wavelet transform for brain signal classification.
Al Ghayab HR; Li Y; Siuly S; Abdulla S
J Neurosci Methods; 2019 Jan; 312():43-52. PubMed ID: 30468823
[TBL] [Abstract][Full Text] [Related]
10. Multichannel Signals Reconstruction Based on Tunable
Li Q; Hu W; Peng E; Liang SY
Entropy (Basel); 2018 Apr; 20(4):. PubMed ID: 33265354
[TBL] [Abstract][Full Text] [Related]
11. Revised Tunable Q-Factor Wavelet Transform for EEG-Based Epileptic Seizure Detection.
Liu Z; Zhu B; Hu M; Deng Z; Zhang J
IEEE Trans Neural Syst Rehabil Eng; 2023 Mar; PP():. PubMed ID: 37028382
[TBL] [Abstract][Full Text] [Related]
12. Classification of myocardial infarction based on hybrid feature extraction and artificial intelligence tools by adopting tunable-Q wavelet transform (TQWT), variational mode decomposition (VMD) and neural networks.
Zeng W; Yuan J; Yuan C; Wang Q; Liu F; Wang Y
Artif Intell Med; 2020 Jun; 106():101848. PubMed ID: 32593387
[TBL] [Abstract][Full Text] [Related]
13. Basis pursuit sparse decomposition using tunable-Q wavelet transform (BPSD-TQWT) for denoising of electrocardiograms.
Srinivasulu A; Sriraam N
Phys Eng Sci Med; 2022 Sep; 45(3):817-833. PubMed ID: 35771386
[TBL] [Abstract][Full Text] [Related]
14. Migraine detection from EEG signals using tunable Q-factor wavelet transform and ensemble learning techniques.
Aslan Z
Phys Eng Sci Med; 2021 Dec; 44(4):1201-1212. PubMed ID: 34505992
[TBL] [Abstract][Full Text] [Related]
15. Stage-independent, single lead EEG sleep spindle detection using the continuous wavelet transform and local weighted smoothing.
Tsanas A; Clifford GD
Front Hum Neurosci; 2015; 9():181. PubMed ID: 25926784
[TBL] [Abstract][Full Text] [Related]
16. Multichannel sleep spindle detection using sparse low-rank optimization.
Parekh A; Selesnick IW; Osorio RS; Varga AW; Rapoport DM; Ayappa I
J Neurosci Methods; 2017 Aug; 288():1-16. PubMed ID: 28600157
[TBL] [Abstract][Full Text] [Related]
17. Sleep spindles and spike-wave discharges in EEG: Their generic features, similarities and distinctions disclosed with Fourier transform and continuous wavelet analysis.
Sitnikova E; Hramov AE; Koronovsky AA; van Luijtelaar G
J Neurosci Methods; 2009 Jun; 180(2):304-16. PubMed ID: 19383511
[TBL] [Abstract][Full Text] [Related]
18. Detection of Myocardial Infarction from Multi-lead ECG using Dual-Q Tunable Q-Factor Wavelet Transform.
Liu J; Zhang C; Ristaniemi T; Cong F
Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():1496-1499. PubMed ID: 31946177
[TBL] [Abstract][Full Text] [Related]
19. Automated detection and localization system of myocardial infarction in single-beat ECG using Dual-Q TQWT and wavelet packet tensor decomposition.
Liu J; Zhang C; Zhu Y; Ristaniemi T; Parviainen T; Cong F
Comput Methods Programs Biomed; 2020 Feb; 184():105120. PubMed ID: 31627147
[TBL] [Abstract][Full Text] [Related]
20. K-complexes Detection in EEG Signals using Fractal and Frequency Features Coupled with an Ensemble Classification Model.
Al-Salman W; Li Y; Wen P
Neuroscience; 2019 Dec; 422():119-133. PubMed ID: 31682947
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]