135 related articles for article (PubMed ID: 25571024)
21. An effective feature extraction method by power spectral density of EEG signal for 2-class motor imagery-based BCI.
Kim C; Sun J; Liu D; Wang Q; Paek S
Med Biol Eng Comput; 2018 Sep; 56(9):1645-1658. PubMed ID: 29497931
[TBL] [Abstract][Full Text] [Related]
22. Efficient Classification of Motor Imagery Electroencephalography Signals Using Deep Learning Methods.
Majidov I; Whangbo T
Sensors (Basel); 2019 Apr; 19(7):. PubMed ID: 30978978
[TBL] [Abstract][Full Text] [Related]
23. Seizure detection from EEG signals using Multivariate Empirical Mode Decomposition.
Zahra A; Kanwal N; Ur Rehman N; Ehsan S; McDonald-Maier KD
Comput Biol Med; 2017 Sep; 88():132-141. PubMed ID: 28719805
[TBL] [Abstract][Full Text] [Related]
24. Spatial filter adaptation based on the divergence framework for motor imagery EEG classification.
Xinyang Li ; Cuntai Guan ; Kai Keng Ang ; Haihong Zhang ; Sim Heng Ong
Annu Int Conf IEEE Eng Med Biol Soc; 2014; 2014():1847-50. PubMed ID: 25570337
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. FBCSP-based Multi-class Motor Imagery Classification using BP and TDP features.
Abbas W; Khan NA
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():215-218. PubMed ID: 30440376
[TBL] [Abstract][Full Text] [Related]
27. Reject option to reduce false prediction rates for EEG-motor imagery based BCI.
Ganeshkumar M; Kai Keng Ang ; So RQ
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():2964-2967. PubMed ID: 29060520
[TBL] [Abstract][Full Text] [Related]
28. [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]
29. 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]
30. 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]
31. Predicting BCI subject performance using probabilistic spatio-temporal filters.
Suk HI; Fazli S; Mehnert J; Müller KR; Lee SW
PLoS One; 2014; 9(2):e87056. PubMed ID: 24551050
[TBL] [Abstract][Full Text] [Related]
32. Tangent Space Features-Based Transfer Learning Classification Model for Two-Class Motor Imagery Brain-Computer Interface.
Gaur P; McCreadie K; Pachori RB; Wang H; Prasad G
Int J Neural Syst; 2019 Dec; 29(10):1950025. PubMed ID: 31711330
[TBL] [Abstract][Full Text] [Related]
33. Noise-assisted multivariate empirical mode decomposition for multichannel EMG signals.
Zhang Y; Xu P; Li P; Duan K; Wen Y; Yang Q; Zhang T; Yao D
Biomed Eng Online; 2017 Aug; 16(1):107. PubMed ID: 28835251
[TBL] [Abstract][Full Text] [Related]
34. Performance evaluation of Noise-Assisted Multivariate Empirical Mode Decomposition and its application to multichannel EMG signals.
Yi Zhang ; Su S; Peng Xu ; Dezhong Yao
Annu Int Conf IEEE Eng Med Biol Soc; 2017 Jul; 2017():3457-3460. PubMed ID: 29060641
[TBL] [Abstract][Full Text] [Related]
35. Spatio-temporal deep learning for EEG-fNIRS brain computer interface.
Ghonchi H; Fateh M; Abolghasemi V; Ferdowsi S; Rezvani M
Annu Int Conf IEEE Eng Med Biol Soc; 2020 Jul; 2020():124-127. PubMed ID: 33017946
[TBL] [Abstract][Full Text] [Related]
36. Comparison of different EEG signal analysis techniques for an offline lower limb motor imagery brain-computer interface.
Ortiz M; Rodriguez-Ugarte M; Iaez E; Azorin JM
Annu Int Conf IEEE Eng Med Biol Soc; 2018 Jul; 2018():203-206. PubMed ID: 30440373
[TBL] [Abstract][Full Text] [Related]
37. Simultaneous brain-computer interfacing and motor control: expanding the reach of non-invasive BCIs.
Cheung W; Sarma D; Scherer R; Rao RP
Annu Int Conf IEEE Eng Med Biol Soc; 2012; 2012():6715-8. PubMed ID: 23367470
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. A neural network-based optimal spatial filter design method for motor imagery classification.
Yuksel A; Olmez T
PLoS One; 2015; 10(5):e0125039. PubMed ID: 25933101
[TBL] [Abstract][Full Text] [Related]
40. A comparative analysis of masking empirical mode decomposition and a neural network with feed-forward and back propagation along with masking empirical mode decomposition to improve the classification performance for a reliable brain-computer interface.
Jaipriya D; Sriharipriya KC
Front Comput Neurosci; 2022; 16():1010770. PubMed ID: 36405787
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
