313 related articles for article (PubMed ID: 26736893)
1. Prediction of motor imagery based brain computer interface performance using a reaction time test.
Darvishi S; Abbott D; Baumert M
Annu Int Conf IEEE Eng Med Biol Soc; 2015 Aug; 2015():2880-3. PubMed ID: 26736893
[TBL] [Abstract][Full Text] [Related]
2. Structural and functional correlates of motor imagery BCI performance: Insights from the patterns of fronto-parietal attention network.
Zhang T; Liu T; Li F; Li M; Liu D; Zhang R; He H; Li P; Gong J; Luo C; Yao D; Xu P
Neuroimage; 2016 Jul; 134():475-485. PubMed ID: 27103137
[TBL] [Abstract][Full Text] [Related]
3. [Execution, assessment and improvement methods of motor imagery for brain-computer interface].
Tian G; Chen J; Ding P; Gong A; Wang F; Luo J; Dong Y; Zhao L; Dang C; Fu Y
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2021 Jun; 38(3):434-446. PubMed ID: 34180188
[TBL] [Abstract][Full Text] [Related]
4. Performance predictors of motor imagery brain-computer interface based on spatial abilities for upper limb rehabilitation.
Pacheco K; Acuna K; Carranza E; Achanccaray D; Andreu-Perez J
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():1014-1017. PubMed ID: 29060046
[TBL] [Abstract][Full Text] [Related]
5. Using a motor imagery questionnaire to estimate the performance of a Brain-Computer Interface based on object oriented motor imagery.
Vuckovic A; Osuagwu BA
Clin Neurophysiol; 2013 Aug; 124(8):1586-95. PubMed ID: 23535455
[TBL] [Abstract][Full Text] [Related]
6. Prediction of Motor Imagery Performance based on Pre-Trial Spatio-Spectral Alertness Features.
Torkamani-Azar M; Jafarifarmand A; Cetin M
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():3062-3065. PubMed ID: 33018651
[TBL] [Abstract][Full Text] [Related]
7. The predictive role of pre-cue EEG rhythms on MI-based BCI classification performance.
Bamdadian A; Guan C; Ang KK; Xu J
J Neurosci Methods; 2014 Sep; 235():138-44. PubMed ID: 24979726
[TBL] [Abstract][Full Text] [Related]
8. Why standard brain-computer interface (BCI) training protocols should be changed: an experimental study.
Jeunet C; Jahanpour E; Lotte F
J Neural Eng; 2016 Jun; 13(3):036024. PubMed ID: 27172246
[TBL] [Abstract][Full Text] [Related]
9. A brain-computer interface driven by imagining different force loads on a single hand: an online feasibility study.
Wang K; Wang Z; Guo Y; He F; Qi H; Xu M; Ming D
J Neuroeng Rehabil; 2017 Sep; 14(1):93. PubMed ID: 28893295
[TBL] [Abstract][Full Text] [Related]
10. Predicting Mental Imagery-Based BCI Performance from Personality, Cognitive Profile and Neurophysiological Patterns.
Jeunet C; N'Kaoua B; Subramanian S; Hachet M; Lotte F
PLoS One; 2015; 10(12):e0143962. PubMed ID: 26625261
[TBL] [Abstract][Full Text] [Related]
11. A Comprehensive Review on Critical Issues and Possible Solutions of Motor Imagery Based Electroencephalography Brain-Computer Interface.
Singh A; Hussain AA; Lal S; Guesgen HW
Sensors (Basel); 2021 Mar; 21(6):. PubMed ID: 33804611
[TBL] [Abstract][Full Text] [Related]
12. Improving motor imagery classification during induced motor perturbations.
Vidaurre C; Jorajuría T; Ramos-Murguialday A; Müller KR; Gómez M; Nikulin VV
J Neural Eng; 2021 Jul; 18(4):. PubMed ID: 34233305
[No Abstract] [Full Text] [Related]
13. Towards increasing the number of commands in a hybrid brain-computer interface with combination of gaze and motor imagery.
Meena YK; Cecotti H; KongFatt Wong-Lin ; Prasad G
Annu Int Conf IEEE Eng Med Biol Soc; 2015 Aug; 2015():506-9. PubMed ID: 26736310
[TBL] [Abstract][Full Text] [Related]
14. Cortical activation and BCI performance during brief tactile imagery: A comparative study with motor imagery.
Sengupta P; Lakshminarayanan K
Behav Brain Res; 2024 Feb; 459():114760. PubMed ID: 37979923
[TBL] [Abstract][Full Text] [Related]
15. Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling.
Lee M; Yoon JG; Lee SW
Front Hum Neurosci; 2020; 14():321. PubMed ID: 32903663
[TBL] [Abstract][Full Text] [Related]
16. Whitening Technique Based on Gram-Schmidt Orthogonalization for Motor Imagery Classification of Brain-Computer Interface Applications.
Choi H; Park J; Yang YM
Sensors (Basel); 2022 Aug; 22(16):. PubMed ID: 36015803
[TBL] [Abstract][Full Text] [Related]
17. Assessing motor imagery in brain-computer interface training: Psychological and neurophysiological correlates.
Vasilyev A; Liburkina S; Yakovlev L; Perepelkina O; Kaplan A
Neuropsychologia; 2017 Mar; 97():56-65. PubMed ID: 28167121
[TBL] [Abstract][Full Text] [Related]
18. User's Self-Prediction of Performance in Motor Imagery Brain-Computer Interface.
Ahn M; Cho H; Ahn S; Jun SC
Front Hum Neurosci; 2018; 12():59. PubMed ID: 29497370
[TBL] [Abstract][Full Text] [Related]
19. Reaction Time Predicts Brain-Computer Interface Aptitude.
Darvishi S; Gharabaghi A; Ridding MC; Abbott D; Baumert M
IEEE J Transl Eng Health Med; 2018; 6():2000311. PubMed ID: 30533323
[TBL] [Abstract][Full Text] [Related]
20. Transcranial magnetic stimulation for individual identification of the best electrode position for a motor imagery-based brain-computer interface.
Hänselmann S; Schneiders M; Weidner N; Rupp R
J Neuroeng Rehabil; 2015 Aug; 12():71. PubMed ID: 26303933
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
