270 related articles for article (PubMed ID: 35978888)
1. A Fused Multidimensional EEG Classification Method Based on an Extreme Tree Feature Selection.
Lin R; Dong C; Ma P; Ma S; Chen X; Liu H
Comput Intell Neurosci; 2022; 2022():7609196. PubMed ID: 35978888
[TBL] [Abstract][Full Text] [Related]
2. The CSP-Based New Features Plus Non-Convex Log Sparse Feature Selection for Motor Imagery EEG Classification.
Zhang S; Zhu Z; Zhang B; Feng B; Yu T; Li Z
Sensors (Basel); 2020 Aug; 20(17):. PubMed ID: 32842635
[TBL] [Abstract][Full Text] [Related]
3. Multi-band spatial feature extraction and classification for motor imaging EEG signals based on OSFBCSP-GAO-SVM model : EEG signal processing.
Shang Y; Gao X; An A
Med Biol Eng Comput; 2023 Jun; 61(6):1581-1602. PubMed ID: 36813927
[TBL] [Abstract][Full Text] [Related]
4. CSP-TSM: Optimizing the performance of Riemannian tangent space mapping using common spatial pattern for MI-BCI.
Kumar S; Mamun K; Sharma A
Comput Biol Med; 2017 Dec; 91():231-242. PubMed ID: 29100117
[TBL] [Abstract][Full Text] [Related]
5. Feature selection using regularized neighbourhood component analysis to enhance the classification performance of motor imagery signals.
Malan NS; Sharma S
Comput Biol Med; 2019 Apr; 107():118-126. PubMed ID: 30802693
[TBL] [Abstract][Full Text] [Related]
6. Temporally Constrained Sparse Group Spatial Patterns for Motor Imagery BCI.
Zhang Y; Nam CS; Zhou G; Jin J; Wang X; Cichocki A
IEEE Trans Cybern; 2019 Sep; 49(9):3322-3332. PubMed ID: 29994667
[TBL] [Abstract][Full Text] [Related]
7. Optimizing spatial patterns with sparse filter bands for motor-imagery based brain-computer interface.
Zhang Y; Zhou G; Jin J; Wang X; Cichocki A
J Neurosci Methods; 2015 Nov; 255():85-91. PubMed ID: 26277421
[TBL] [Abstract][Full Text] [Related]
8. Improving classification accuracy of motor imagery EEG using genetic feature selection.
Hsu WY
Clin EEG Neurosci; 2014 Jul; 45(3):163-8. PubMed ID: 24048242
[TBL] [Abstract][Full Text] [Related]
9. Feature Selection Using Extreme Gradient Boosting Bayesian Optimization to upgrade the Classification Performance of Motor Imagery signals for BCI.
Thenmozhi T; Helen R
J Neurosci Methods; 2022 Jan; 366():109425. PubMed ID: 34838951
[TBL] [Abstract][Full Text] [Related]
10. Classification of multi-class motor imagery with a novel hierarchical SVM algorithm for brain-computer interfaces.
Dong E; Li C; Li L; Du S; Belkacem AN; Chen C
Med Biol Eng Comput; 2017 Oct; 55(10):1809-1818. PubMed ID: 28238175
[TBL] [Abstract][Full Text] [Related]
11. A novel method for classification of multi-class motor imagery tasks based on feature fusion.
Hou Y; Chen T; Lun X; Wang F
Neurosci Res; 2022 Mar; 176():40-48. PubMed ID: 34508756
[TBL] [Abstract][Full Text] [Related]
12. Assembling A Multi-Feature EEG Classifier for Left-Right Motor Imagery Data Using Wavelet-Based Fuzzy Approximate Entropy for Improved Accuracy.
Hsu WY
Int J Neural Syst; 2015 Dec; 25(8):1550037. PubMed ID: 26584583
[TBL] [Abstract][Full Text] [Related]
13. A Computationally Efficient Multiclass Time-Frequency Common Spatial Pattern Analysis on EEG Motor Imagery.
Zhang C; Eskandarian A
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():514-518. PubMed ID: 33018040
[TBL] [Abstract][Full Text] [Related]
14. Study of MI-BCI classification method based on the Riemannian transform of personalized EEG spatiotemporal features.
Ding X; Yang L; Li C
Math Biosci Eng; 2023 May; 20(7):12454-12471. PubMed ID: 37501450
[TBL] [Abstract][Full Text] [Related]
15. Class discrepancy-guided sub-band filter-based common spatial pattern for motor imagery classification.
Luo J; Wang J; Xu R; Xu K
J Neurosci Methods; 2019 Jul; 323():98-107. PubMed ID: 31141703
[TBL] [Abstract][Full Text] [Related]
16. An EEG channel selection method for motor imagery based brain-computer interface and neurofeedback using Granger causality.
Varsehi H; Firoozabadi SMP
Neural Netw; 2021 Jan; 133():193-206. PubMed ID: 33220643
[TBL] [Abstract][Full Text] [Related]
17. Online detection of class-imbalanced error-related potentials evoked by motor imagery.
Liu Q; Zheng W; Chen K; Ma L; Ai Q
J Neural Eng; 2021 Apr; 18(4):. PubMed ID: 33823492
[No Abstract] [Full Text] [Related]
18. Major Depression Detection from EEG Signals Using Kernel Eigen-Filter-Bank Common Spatial Patterns.
Liao SC; Wu CT; Huang HC; Cheng WT; Liu YH
Sensors (Basel); 2017 Jun; 17(6):. PubMed ID: 28613237
[TBL] [Abstract][Full Text] [Related]
19. Motor imagery classification using geodesic filtering common spatial pattern and filter-bank feature weighted support vector machine.
Wang F; Xu Z; Zhang W; Wu S; Zhang Y; Ping J; Wu C
Rev Sci Instrum; 2020 Mar; 91(3):034106. PubMed ID: 32259927
[TBL] [Abstract][Full Text] [Related]
20. Motor imagery EEG classification based on ensemble support vector learning.
Luo J; Gao X; Zhu X; Wang B; Lu N; Wang J
Comput Methods Programs Biomed; 2020 Sep; 193():105464. PubMed ID: 32283387
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]