356 related articles for article (PubMed ID: 32187208)
1. Toward a compact hybrid brain-computer interface (BCI): Performance evaluation of multi-class hybrid EEG-fNIRS BCIs with limited number of channels.
Kwon J; Shin J; Im CH
PLoS One; 2020; 15(3):e0230491. PubMed ID: 32187208
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. A Ternary Hybrid EEG-NIRS Brain-Computer Interface for the Classification of Brain Activation Patterns during Mental Arithmetic, Motor Imagery, and Idle State.
Shin J; Kwon J; Im CH
Front Neuroinform; 2018; 12():5. PubMed ID: 29527160
[TBL] [Abstract][Full Text] [Related]
4. Improvement of Information Transfer Rates Using a Hybrid EEG-NIRS Brain-Computer Interface with a Short Trial Length: Offline and Pseudo-Online Analyses.
Shin J; Kim DW; Müller KR; Hwang HJ
Sensors (Basel); 2018 Jun; 18(6):. PubMed ID: 29874804
[TBL] [Abstract][Full Text] [Related]
5. Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.
Chiarelli AM; Croce P; Merla A; Zappasodi F
J Neural Eng; 2018 Jun; 15(3):036028. PubMed ID: 29446352
[TBL] [Abstract][Full Text] [Related]
6. A Computationally Efficient Method for Hybrid EEG-fNIRS BCI Based on the Pearson Correlation.
Hasan MAH; Khan MU; Mishra D
Biomed Res Int; 2020; 2020():1838140. PubMed ID: 32923476
[TBL] [Abstract][Full Text] [Related]
7. Hybrid EEG-fNIRS Asynchronous Brain-Computer Interface for Multiple Motor Tasks.
Buccino AP; Keles HO; Omurtag A
PLoS One; 2016; 11(1):e0146610. PubMed ID: 26730580
[TBL] [Abstract][Full Text] [Related]
8. Cortical effects of user training in a motor imagery based brain-computer interface measured by fNIRS and EEG.
Kaiser V; Bauernfeind G; Kreilinger A; Kaufmann T; Kübler A; Neuper C; Müller-Putz GR
Neuroimage; 2014 Jan; 85 Pt 1():432-44. PubMed ID: 23651839
[TBL] [Abstract][Full Text] [Related]
9. A Graph-Based Nonlinear Dynamic Characterization of Motor Imagery Toward an Enhanced Hybrid BCI.
Hosni SMI; Borgheai SB; McLinden J; Zhu S; Huang X; Ostadabbas S; Shahriari Y
Neuroinformatics; 2022 Oct; 20(4):1169-1189. PubMed ID: 35907174
[TBL] [Abstract][Full Text] [Related]
10. Eyes-closed hybrid brain-computer interface employing frontal brain activation.
Shin J; Müller KR; Hwang HJ
PLoS One; 2018; 13(5):e0196359. PubMed ID: 29734383
[TBL] [Abstract][Full Text] [Related]
11. FGANet: fNIRS-Guided Attention Network for Hybrid EEG-fNIRS Brain-Computer Interfaces.
Kwak Y; Song WJ; Kim SE
IEEE Trans Neural Syst Rehabil Eng; 2022; 30():329-339. PubMed ID: 35130163
[TBL] [Abstract][Full Text] [Related]
12. Evaluating a four-class motor-imagery-based optical brain-computer interface.
Batula AM; Ayaz H; Kim YE
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():2000-3. PubMed ID: 25570375
[TBL] [Abstract][Full Text] [Related]
13. Application of a common spatial pattern-based algorithm for an fNIRS-based motor imagery brain-computer interface.
Zhang S; Zheng Y; Wang D; Wang L; Ma J; Zhang J; Xu W; Li D; Zhang D
Neurosci Lett; 2017 Aug; 655():35-40. PubMed ID: 28663052
[TBL] [Abstract][Full Text] [Related]
14. Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review.
Khan H; Naseer N; Yazidi A; Eide PK; Hassan HW; Mirtaheri P
Front Hum Neurosci; 2020; 14():613254. PubMed ID: 33568979
[TBL] [Abstract][Full Text] [Related]
15. Enhancing Performance of a Hybrid EEG-fNIRS System Using Channel Selection and Early Temporal Features.
Li R; Potter T; Huang W; Zhang Y
Front Hum Neurosci; 2017; 11():462. PubMed ID: 28966581
[TBL] [Abstract][Full Text] [Related]
16. Classification of prefrontal and motor cortex signals for three-class fNIRS-BCI.
Hong KS; Naseer N; Kim YH
Neurosci Lett; 2015 Feb; 587():87-92. PubMed ID: 25529197
[TBL] [Abstract][Full Text] [Related]
17. A novel motor imagery hybrid brain computer interface using EEG and functional transcranial Doppler ultrasound.
Khalaf A; Sejdic E; Akcakaya M
J Neurosci Methods; 2019 Feb; 313():44-53. PubMed ID: 30590086
[TBL] [Abstract][Full Text] [Related]
18. A Stimulus-Independent Hybrid BCI Based on Motor Imagery and Somatosensory Attentional Orientation.
Yao L; Sheng X; Zhang D; Jiang N; Mrachacz-Kersting N; Zhu X; Farina D
IEEE Trans Neural Syst Rehabil Eng; 2017 Sep; 25(9):1674-1682. PubMed ID: 28328506
[TBL] [Abstract][Full Text] [Related]
19. Towards optimal visual presentation design for hybrid EEG-fTCD brain-computer interfaces.
Khalaf A; Sejdic E; Akcakaya M
J Neural Eng; 2018 Oct; 15(5):056019. PubMed ID: 30021931
[TBL] [Abstract][Full Text] [Related]
20. Crossing time windows optimization based on mutual information for hybrid BCI.
Meng M; Dai L; She Q; Ma Y; Kong W
Math Biosci Eng; 2021 Sep; 18(6):7919-7935. PubMed ID: 34814281
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]