Motor Imagery Brain-Computer Interface Classification Algorithm Based on Spatiotemporal Feature Fusion and Convolutional Neural Networks

Συγγραφείς: Bao, Naqin, Kang, Hongzhuo, Liu, Huanzi, Dong, Chaoyi, Lei, Dongyang, Chen, Xiaoyan

Πηγή: 2025 37th Chinese Control and Decision Conference (CCDC) Chinese Control and Decision Conference (CCDC), 2025 37th. :1251-1256 May, 2025

Relation: 2025 37th Chinese Control and Decision Conference (CCDC)

Research on Brain-Computer Interface Classification Algorithm Supported by Motion Imagination

Συγγραφείς: Jin, Hulin, Jin, Zhiran, Kim, Yong-Guk, Zhou, Yutong, Zhang, Kang

Πηγή: 2025 4th International Symposium on Computer Applications and Information Technology (ISCAIT) Computer Applications and Information Technology (ISCAIT), 2025 4th International Symposium on. :978-982 Mar, 2025

Relation: 2025 4th International Symposium on Computer Applications and Information Technology (ISCAIT)

Variational Phasor Circuits for Phase-Native Brain-Computer Interface Classification

Συγγραφείς: Sigdel, Dibakar

Θεματικοί όροι: Machine Learning

Σύνδεσμος πρόσβασης: https://arxiv.org/abs/2603.18078

A novel motor imagery brain-computer interface classification framework based on augmented covariance matrix: deep Riemannian geometry learning with self-attention mechanism

Συγγραφείς: Yan, Tian^Aff1, Zhang, Aimin^Aff1, Yang, Zengyao^Aff2, Su, Hechong^Aff3, Ma, Yidan^Aff1, Wu, Yue^Aff1, Yan, Li^Aff4, Wang, Yichen^Aff5, Guo, Fei^Aff6, Cao, Jianfu^{Aff1, IDs11571026105487_cor1}

Πηγή: Cognitive Neurodynamics. 20(1)

Data augmentation and feature extraction using deep learning for motor imagery EEG-based brain–computer interface classification

Συγγραφείς: Anjerani, Marzieh^Aff1, Pedram, Mir Mohsen^{Aff2, IDs00521025114032_cor1}, Mirzarezaee, Mitra^{Aff1, IDs00521025114032_cor2}

Πηγή: Neural Computing and Applications. 37(23):19339-19369

Research on P300 Brain-Computer Interface Classification Algorithm Combining Channel Selection and Deep Learning

Συγγραφείς: Li, Qi, Sun, Meiqi, Song, Yu, Sun, Jiajun

Πηγή: 2022 16th ICME International Conference on Complex Medical Engineering (CME) Complex Medical Engineering (CME), 2022 16th ICME International Conference on. :298-301 Nov, 2022

Relation: 2022 16th ICME International Conference on Complex Medical Engineering (CME)

Boosting motor imagery brain-computer interface classification using multiband and hybrid feature extraction

Συγγραφείς: Moufassih, Mustapha^{Aff1, IDs11042023171187_cor1}, Tarahi, Ousama^Aff1, Hamou, Soukaina^Aff1, Agounad, Said^Aff1, Idrissi Azami, Hafida^Aff1

Πηγή: Multimedia Tools and Applications: An International Journal. 83(16):49441-49472

Binarization Methods for Motor-Imagery Brain–Computer Interface Classification

Συγγραφείς: Hersche, M., Benini, L., Rahimi, A.

Πηγή: IEEE Journal on Emerging and Selected Topics in Circuits and Systems IEEE J. Emerg. Sel. Topics Circuits Syst. Emerging and Selected Topics in Circuits and Systems, IEEE Journal on. 10(4):567-577 Dec, 2020

Robust Motor Imagery–Brain–Computer Interface Classification in Signal Degradation: A Multi-Window Ensemble Approach.

Συγγραφείς: Lee, Dong-Geun¹ (AUTHOR), Lee, Seung-Bo¹ (AUTHOR) koreateam23@gmail.com

Πηγή: Biomimetics (2313-7673). Dec2025, Vol. 10 Issue 12, p832. 16p.

Θεματικοί όροι: *Brain-computer interfaces, *Electroencephalography, *Classification, *Motor imagery (Cognition), *Electronic modulation, *Interference (Telecommunication), *Robust statistics

Geometric Features for Brain-Computer Interface Classification: Benchmark Results on PhysioNet Motor Imagery

Συγγραφείς: OmniSciences Research

Θεματικοί όροι: symmetric positive-definite matrices, motor imagery, geometric features, brain-computer interface, PhysioNet, covariance matrices, EEG, BCI, Riemannian geometry

Geometric Features for Brain-Computer Interface Classification: Benchmark Results on PhysioNet Motor Imagery

Συγγραφείς: Austermann, Sloan

Θεματικοί όροι: symmetric positive-definite matrices, motor imagery, geometric features, brain-computer interface, PhysioNet, covariance matrices, EEG, BCI, Riemannian geometry

Comparison of the Performance of Traditional Machine Learning and Deep Learning Models in Real-Time Brain-Computer Interface Classification

Additional Titles: Jämförelse av prestandan hos traditionella maskininlärningsmodeller och djupinlärningsmodeller i realtidsklassificering inom hjärn-datorgränssnitt

Συγγραφείς: Stange, Ossian, Stenberg, Oliver

Όροι ευρετηρίου: Computer and Information Sciences, Data- och informationsvetenskap, Student thesis, info:eu-repo/semantics/bachelorThesis, text

Σύνδεσμος: http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-367552
TRITA-EECS-EX ; 2025:272

Automatic EEG channel selection for multiclass brain-computer interface classification using multiobjective improved firefly algorithm

Συγγραφείς: Tiwari, Anurag^{Aff1, IDs11042022127952_cor1}, Chaturvedi, Amrita^Aff1

Πηγή: Multimedia Tools and Applications: An International Journal. 82(4):5405-5433

A study of kernel CSP-based motor imagery brain computer interface classification

Συγγραφείς: Albalawi, Hassan, Song, Xiaomu

Πηγή: 2012 IEEE Signal Processing in Medicine and Biology Symposium (SPMB) Signal Processing in Medicine and Biology Symposium (SPMB), 2012 IEEE. :1-4 Dec, 2012

Relation: 2012 IEEE Signal Processing in Medicine and Biology Symposium (SPMB)

Binarization Methods for Motor-Imagery Brain-Computer Interface Classification

Συγγραφείς: Hersche, Michael, Benini, Luca, Rahimi, Abbas

Θεματικοί όροι: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Machine Learning

Σύνδεσμος πρόσβασης: http://arxiv.org/abs/2010.07004

Subspace-constrained multilinear discriminant analysis for ERP-based brain computer interface classification

Συγγραφείς: Higashi, Hiroshi, Rutkowski, Tomasz M., Tanaka, Toshihisa, Tanaka, Yuichi

Πηγή: 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA) Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2015 Asia-Pacific. :934-940 Dec, 2015

Relation: 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

Pre-Stimulus Sensorimotor Rhythms Influence Brain–Computer Interface Classification Performance

Συγγραφείς: Maeder, C. L., Sannelli, C., Haufe, S., Blankertz, B.

Πηγή: IEEE Transactions on Neural Systems and Rehabilitation Engineering IEEE Trans. Neural Syst. Rehabil. Eng. Neural Systems and Rehabilitation Engineering, IEEE Transactions on. 20(5):653-662 Sep, 2012

Multiclass Brain–Computer Interface Classification by Riemannian Geometry

Συγγραφείς: Barachant, A., Bonnet, S., Congedo, M., Jutten, C.

Πηγή: IEEE Transactions on Biomedical Engineering IEEE Trans. Biomed. Eng. Biomedical Engineering, IEEE Transactions on. 59(4):920-928 Apr, 2012

A review on transfer learning for brain-computer interface classification

Συγγραφείς: Wang, Peitao, Lu, Jun, Zhang, Bin, Tang, Zeng

Πηγή: 2015 5th International Conference on Information Science and Technology (ICIST) Information Science and Technology (ICIST), 2015 5th International Conference on. :315-322 Apr, 2015

Relation: 2015 5th International Conference on Information Science and Technology (ICIST)

A Greedy Feature Selection Algorithm for Brain-Computer Interface Classification Committees

Συγγραφείς: Trofimov, Alexander G. ¹, Shishkin, Sergei L. ², Kozyrskiy, Bogdan L. ^{1, 2}, Velichkovsky, Boris M. ²

Πηγή: In Procedia Computer Science 2018 123:488-493