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Multiclass Brain-Computer Interface Classification by Riemannian Geometry
Barachant, Alexandre, Bonnet, Stéphane, Congedo, Marco, Jutten, Christian
Published in IEEE transactions on biomedical engineering (01.04.2012)
Published in IEEE transactions on biomedical engineering (01.04.2012)
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Journal Article
Evidence of Variabilities in EEG Dynamics During Motor Imagery-Based Multiclass Brain-Computer Interface
Saha, Simanto, Ahmed, Khawza Iftekhar Uddin, Mostafa, Raqibul, Hadjileontiadis, Leontios, Khandoker, Ahsan
Published in IEEE transactions on neural systems and rehabilitation engineering (01.02.2018)
Published in IEEE transactions on neural systems and rehabilitation engineering (01.02.2018)
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Journal Article
A novel Morse code-inspired method for multiclass motor imagery brain–computer interface (BCI) design
Jiang, Jun, Zhou, Zongtan, Yin, Erwei, Yu, Yang, Liu, Yadong, Hu, Dewen
Published in Computers in biology and medicine (01.11.2015)
Published in Computers in biology and medicine (01.11.2015)
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Journal Article
Use of covariance matrix images for electroencephalography signal classification for multiclass motor imagery‐based brain computer interface
Thrikkannoor Kolathod, Muhamed Jishad, Sanjay, M.
Published in International journal of imaging systems and technology (01.01.2024)
Published in International journal of imaging systems and technology (01.01.2024)
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Journal Article
Adaptive semi-supervised classification to reduce intersession non-stationarity in multiclass motor imagery-based brain–computer interfaces
Nicolas-Alonso, Luis F., Corralejo, Rebeca, Gomez-Pilar, Javier, Álvarez, Daniel, Hornero, Roberto
Published in Neurocomputing (Amsterdam) (02.07.2015)
Published in Neurocomputing (Amsterdam) (02.07.2015)
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Journal Article
An auditory multiclass brain-computer interface with natural stimuli: Usability evaluation with healthy participants and a motor impaired end user
Simon, Nadine, Käthner, Ivo, Ruf, Carolin A., Pasqualotto, Emanuele, Kübler, Andrea, Halder, Sebastian
Published in Frontiers in human neuroscience (09.01.2015)
Published in Frontiers in human neuroscience (09.01.2015)
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Journal Article
Enhanced Accuracy for Multiclass Mental Workload Detection Using Long Short-Term Memory for Brain–Computer Interface
Asgher, Umer, Khalil, Khurram, Khan, Muhammad Jawad, Ahmad, Riaz, Butt, Shahid Ikramullah, Ayaz, Yasar, Naseer, Noman, Nazir, Salman
Published in Frontiers in neuroscience (23.06.2020)
Published in Frontiers in neuroscience (23.06.2020)
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Journal Article
Adaptive Stacked Generalization for Multiclass Motor Imagery-Based Brain Computer Interfaces
Nicolas-Alonso, Luis F., Corralejo, Rebeca, Gomez-Pilar, Javier, Alvarez, Daniel, Hornero, Roberto
Published in IEEE transactions on neural systems and rehabilitation engineering (01.07.2015)
Published in IEEE transactions on neural systems and rehabilitation engineering (01.07.2015)
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Journal Article
Formulating Divergence Framework for Multiclass Motor Imagery EEG Brain Computer Interface
Kumar, Satyam, Reddy, Tharun Kumar, Arora, Vipul, Behera, Laxmidhar
Published in Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) (01.05.2020)
Published in Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) (01.05.2020)
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Conference Proceeding
Improving classification performance of four class FNIRS-BCI using Mel Frequency Cepstral Coefficients (MFCC)
Ghaffar, Muhammad Saad Bin Abdul, Khan, Umar S., Iqbal, J., Rashid, Nasir, Hamza, Amir, Qureshi, Waqar S., Tiwana, Mohsin I., Izhar, U.
Published in Infrared physics & technology (01.01.2021)
Published in Infrared physics & technology (01.01.2021)
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Journal Article
Improvement of classification accuracy in a phase-tagged steady-state visual evoked potential-based brain computer interface using multiclass support vector machine
Yeh, Chia-Lung, Lee, Po-Lei, Chen, Wei-Ming, Chang, Chun-Yen, Wu, Yu-Te, Lan, Gong-Yau
Published in Biomedical engineering online (21.05.2013)
Published in Biomedical engineering online (21.05.2013)
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Journal Article