185 related articles for article (PubMed ID: 29046111)
1. EEG Classification with a Sequential Decision-Making Method in Motor Imagery BCI.
Liu R; Wang Y; Newman GI; Thakor NV; Ying S
Int J Neural Syst; 2017 Dec; 27(8):1750046. PubMed ID: 29046111
[TBL] [Abstract][Full Text] [Related]
2. Sequential Probability Ratio Testing with Power Projective Base Method Improves Decision-Making for BCI.
Liu R; Wang Y; Wu X; Cheng J
Comput Math Methods Med; 2017; 2017():2948742. PubMed ID: 29348781
[TBL] [Abstract][Full Text] [Related]
3. Decision tree structure based classification of EEG signals recorded during two dimensional cursor movement imagery.
Aydemir O; Kayikcioglu T
J Neurosci Methods; 2014 May; 229():68-75. PubMed ID: 24751647
[TBL] [Abstract][Full Text] [Related]
4. A fresh look at functional link neural network for motor imagery-based brain-computer interface.
Hettiarachchi IT; Babaei T; Nguyen T; Lim CP; Nahavandi S
J Neurosci Methods; 2018 Jul; 305():28-35. PubMed ID: 29733940
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier-based approach.
Miao M; Zeng H; Wang A; Zhao C; Liu F
J Neurosci Methods; 2017 Feb; 278():13-24. PubMed ID: 28012854
[TBL] [Abstract][Full Text] [Related]
7. Sparse Bayesian Learning for Obtaining Sparsity of EEG Frequency Bands Based Feature Vectors in Motor Imagery Classification.
Zhang Y; Wang Y; Jin J; Wang X
Int J Neural Syst; 2017 Mar; 27(2):1650032. PubMed ID: 27377661
[TBL] [Abstract][Full Text] [Related]
8. Classification of electroencephalogram signals using wavelet-CSP and projection extreme learning machine.
Dai Y; Zhang X; Chen Z; Xu X
Rev Sci Instrum; 2018 Jul; 89(7):074302. PubMed ID: 30068128
[TBL] [Abstract][Full Text] [Related]
9. Online EEG Classification of Covert Speech for Brain-Computer Interfacing.
Sereshkeh AR; Trott R; Bricout A; Chau T
Int J Neural Syst; 2017 Dec; 27(8):1750033. PubMed ID: 28830308
[TBL] [Abstract][Full Text] [Related]
10. Adaptive power projection method for accumulative EEG classification.
Li CY; Liu R; Wang YY; Wang YX; Li X
Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():7052-5. PubMed ID: 24111369
[TBL] [Abstract][Full Text] [Related]
11. A flexible analytic wavelet transform based approach for motor-imagery tasks classification in BCI applications.
Chaudhary S; Taran S; Bajaj V; Siuly S
Comput Methods Programs Biomed; 2020 Apr; 187():105325. PubMed ID: 31964514
[TBL] [Abstract][Full Text] [Related]
12. The backtracking search optimization algorithm for frequency band and time segment selection in motor imagery-based brain-computer interfaces.
Wei Z; Wei Q
J Integr Neurosci; 2016 Sep; 15(3):347-364. PubMed ID: 27681162
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Space-time recurrences for functional connectivity evaluation and feature extraction in motor imagery brain-computer interfaces.
Rodrigues PG; Filho CAS; Attux R; Castellano G; Soriano DC
Med Biol Eng Comput; 2019 Aug; 57(8):1709-1725. PubMed ID: 31127535
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. 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]
17. A self produced mother wavelet feature extraction method for motor imagery brain-computer interface.
Yeh WL; Huang YC; Chiou JH; Duann JR; Chiou JC
Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():4302-5. PubMed ID: 24110684
[TBL] [Abstract][Full Text] [Related]
18. Single trial classification of motor imagination using 6 dry EEG electrodes.
Popescu F; Fazli S; Badower Y; Blankertz B; Müller KR
PLoS One; 2007 Jul; 2(7):e637. PubMed ID: 17653264
[TBL] [Abstract][Full Text] [Related]
19. Classification of brain signals associated with imagination of hand grasping, opening and reaching by means of wavelet-based common spatial pattern and mutual information.
Amanpour B; Erfanian A
Annu Int Conf IEEE Eng Med Biol Soc; 2013; 2013():2224-7. PubMed ID: 24110165
[TBL] [Abstract][Full Text] [Related]
20. [Three-class Motor Imagery Classification Based on Optimal Sub-band Features of Independent Components].
Kang S; Zhou B; Wu X
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2016 Apr; 33(2):208-15. PubMed ID: 29708317
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
