MI brain-computer interfaces: A concise overview
SK Mandal, MNBJ Naskar - Biomedical Signal Processing and Control, 2023 - Elsevier
BCI stands for brain–computer interface, and this is the hottest topic among the research
community to convert brain impulses into preset instructions that can be used to interact with …
community to convert brain impulses into preset instructions that can be used to interact with …
Learning optimal time-frequency-spatial features by the cissa-csp method for motor imagery eeg classification
H Hu, Z Pu, H Li, Z Liu, P Wang - Sensors, 2022 - mdpi.com
The common spatial pattern (CSP) is a popular method in feature extraction for motor
imagery (MI) electroencephalogram (EEG) classification in brain–computer interface (BCI) …
imagery (MI) electroencephalogram (EEG) classification in brain–computer interface (BCI) …
An IoT-Based Intelligent Selection of Multidomain Feature for Smart Healthcare Using Reinforcement Learning in Schizophrenia
X Li, H Huang - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
Currently, the health industry by the Internet of Things (IoT) is develo** rapidly, and
electroencephalogram (EEG) signal has become a bridge for human–machine …
electroencephalogram (EEG) signal has become a bridge for human–machine …
Multi-domain feature joint optimization based on multi-view learning for improving the EEG decoding
B Shi, Z Yue, S Yin, J Zhao, J Wang - Frontiers in Human …, 2023 - frontiersin.org
Background Brain-computer interface (BCI) systems based on motor imagery (MI) have
been widely used in neurorehabilitation. Feature extraction applied by the common spatial …
been widely used in neurorehabilitation. Feature extraction applied by the common spatial …
Optimal channel and frequency band‐based feature selection for motor imagery electroencephalogram classification
Common spatial pattern (CSP) is a widely adopted method for electroencephalogram (EEG)
feature extraction in brain‐computer interface (BCI) based on motor imagery. Bandpass …
feature extraction in brain‐computer interface (BCI) based on motor imagery. Bandpass …
A robust multi-branch multi-attention-mechanism EEGNet for motor imagery BCI decoding
H Deng, M Li, J Li, M Guo, G Xu - Journal of Neuroscience Methods, 2024 - Elsevier
Abstract Background Motor-Imagery-based Brain-Computer Interface (MI-BCI) is a promising
technology to assist communication, movement, and neurological rehabilitation for motor …
technology to assist communication, movement, and neurological rehabilitation for motor …
GMMPLS: a novel automatic state-based algorithm for continuous decoding in BMIs
In this paper, a novel fully-automated state-based decoding method has been proposed for
continuous decoding problems in brain-machine interface (BMI) systems, called Gaussian …
continuous decoding problems in brain-machine interface (BMI) systems, called Gaussian …
Closed loop BCI system for Cybathlon 2020
ABSTRACT We developed a Brain-Computer Interface (BCI) System for the BCI discipline of
Cybathlon 2020 competition, where participants with tetraplegia (pilots) control a computer …
Cybathlon 2020 competition, where participants with tetraplegia (pilots) control a computer …
EBi-LSTM: an enhanced bi-directional LSTM for time-series data classification by heuristic development of optimal feature integration in brain computer interface
Generally, time series data is referred to as the sequential representation of data that
observes from different applications. Therefore, such expertise can use …
observes from different applications. Therefore, such expertise can use …
An optimized GMM algorithm and its application in single-trial motor imagination recognition
R Fu, Z Li, J Wang - Biomedical Signal Processing and Control, 2022 - Elsevier
The Gaussian mixture model (GMM) is utilized to illustrate the possibility of applying
probabilistic models to data clustering and provide an efficient method for processing EEG …
probabilistic models to data clustering and provide an efficient method for processing EEG …