229 related articles for article (PubMed ID: 25977685)
1. Feature Selection Applying Statistical and Neurofuzzy Methods to EEG-Based BCI.
Martinez-Leon JA; Cano-Izquierdo JM; Ibarrola J
Comput Intell Neurosci; 2015; 2015():781207. PubMed ID: 25977685
[TBL] [Abstract][Full Text] [Related]
2. Improving motor imagery classification with a new BCI design using neuro-fuzzy S-dFasArt.
Cano-Izquierdo JM; Ibarrola J; Almonacid M
IEEE Trans Neural Syst Rehabil Eng; 2012 Jan; 20(1):2-7. PubMed ID: 21997321
[TBL] [Abstract][Full Text] [Related]
3. Improving classification accuracy using fuzzy method for BCI signals.
Wei Y; Jun Y; Lin S; Hong L
Biomed Mater Eng; 2014; 24(6):2937-43. PubMed ID: 25227000
[TBL] [Abstract][Full Text] [Related]
4. Modified CC-LR algorithm with three diverse feature sets for motor imagery tasks classification in EEG based brain-computer interface.
Siuly ; Li Y; Paul Wen P
Comput Methods Programs Biomed; 2014 Mar; 113(3):767-80. PubMed ID: 24440135
[TBL] [Abstract][Full Text] [Related]
5. Classification of motor imagery tasks for BCI with multiresolution analysis and multiobjective feature selection.
Ortega J; Asensio-Cubero J; Gan JQ; Ortiz A
Biomed Eng Online; 2016 Jul; 15 Suppl 1(Suppl 1):73. PubMed ID: 27454531
[TBL] [Abstract][Full Text] [Related]
6. A hybrid NIRS-EEG system for self-paced brain computer interface with online motor imagery.
Koo B; Lee HG; Nam Y; Kang H; Koh CS; Shin HC; Choi S
J Neurosci Methods; 2015 Apr; 244():26-32. PubMed ID: 24797225
[TBL] [Abstract][Full Text] [Related]
7. An embedded implementation based on adaptive filter bank for brain-computer interface systems.
Belwafi K; Romain O; Gannouni S; Ghaffari F; Djemal R; Ouni B
J Neurosci Methods; 2018 Jul; 305():1-16. PubMed ID: 29738806
[TBL] [Abstract][Full Text] [Related]
8. Separable Common Spatio-Spectral Patterns for Motor Imagery BCI Systems.
Aghaei AS; Mahanta MS; Plataniotis KN
IEEE Trans Biomed Eng; 2016 Jan; 63(1):15-29. PubMed ID: 26452197
[TBL] [Abstract][Full Text] [Related]
9. Uncorrelated multiway discriminant analysis for motor imagery EEG classification.
Liu Y; Zhao Q; Zhang L
Int J Neural Syst; 2015 Jun; 25(4):1550013. PubMed ID: 25986750
[TBL] [Abstract][Full Text] [Related]
10. A hybrid BCI based on EEG and fNIRS signals improves the performance of decoding motor imagery of both force and speed of hand clenching.
Yin X; Xu B; Jiang C; Fu Y; Wang Z; Li H; Shi G
J Neural Eng; 2015 Jun; 12(3):036004. PubMed ID: 25834118
[TBL] [Abstract][Full Text] [Related]
11. A Quasi-probabilistic distribution model for EEG Signal classification by using 2-D signal representation.
Murat Yilmaz C; Kose C; Hatipoglu B
Comput Methods Programs Biomed; 2018 Aug; 162():187-196. PubMed ID: 29903485
[TBL] [Abstract][Full Text] [Related]
12. Faster self-organizing fuzzy neural network training and a hyperparameter analysis for a brain-computer interface.
Coyle D; Prasad G; McGinnity TM
IEEE Trans Syst Man Cybern B Cybern; 2009 Dec; 39(6):1458-71. PubMed ID: 19493851
[TBL] [Abstract][Full Text] [Related]
13. Relevant Feature Selection from a Combination of Spectral-Temporal and Spatial Features for Classification of Motor Imagery EEG.
Kirar JS; Agrawal RK
J Med Syst; 2018 Mar; 42(5):78. PubMed ID: 29546648
[TBL] [Abstract][Full Text] [Related]
14. A Wearable Channel Selection-Based Brain-Computer Interface for Motor Imagery Detection.
Lo CC; Chien TY; Chen YC; Tsai SH; Fang WC; Lin BS
Sensors (Basel); 2016 Feb; 16(2):213. PubMed ID: 26861347
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. A new parameter tuning approach for enhanced motor imagery EEG signal classification.
Kumar S; Sharma A
Med Biol Eng Comput; 2018 Oct; 56(10):1861-1874. PubMed ID: 29616456
[TBL] [Abstract][Full Text] [Related]
17. Tensor Discriminant Analysis for MI-EEG Signal Classification Using Convolutional Neural Network.
Huang S; Peng H; Chen Y; Sun K; Shen F; Wang T; Ma T
Annu Int Conf IEEE Eng Med Biol Soc; 2019 Jul; 2019():5971-5974. PubMed ID: 31947207
[TBL] [Abstract][Full Text] [Related]
18. A novel Morse code-inspired method for multiclass motor imagery brain-computer interface (BCI) design.
Jiang J; Zhou Z; Yin E; Yu Y; Liu Y; Hu D
Comput Biol Med; 2015 Nov; 66():11-9. PubMed ID: 26340647
[TBL] [Abstract][Full Text] [Related]
19. 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]
20. EEG-based motor imagery classification using neuro-fuzzy prediction and wavelet fractal features.
Hsu WY
J Neurosci Methods; 2010 Jun; 189(2):295-302. PubMed ID: 20381529
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
