Discriminative spatial-frequency-temporal feature extraction and classification of motor imagery EEG: An sparse regression and Weighted Naïve Bayesian Classifier …
M Miao, H Zeng, A Wang, C Zhao, F Liu - Journal of neuroscience methods, 2017 - Elsevier
Background Common spatial pattern (CSP) is most widely used in motor imagery based
brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the …
brain-computer interface (BCI) systems. In conventional CSP algorithm, pairs of the …
A comprehensive review of the movement imaginary brain-computer interface methods: Challenges and future directions
Brain-computer interface (BCI) aims to translate human intention into a control output signal.
In motor-imaginary (MI) BCI, the imagination of movement modifies the cortex brain activity …
In motor-imaginary (MI) BCI, the imagination of movement modifies the cortex brain activity …
Adaptive stacked generalization for multiclass motor imagery-based brain computer interfaces
LF Nicolas-Alonso, R Corralejo… - … on Neural Systems …, 2015 - ieeexplore.ieee.org
Practical motor imagery-based brain computer interface (MI-BCI) applications are limited by
the difficult to decode brain signals in a reliable way. In this paper, we propose a processing …
the difficult to decode brain signals in a reliable way. In this paper, we propose a processing …
A spatial-frequency-temporal optimized feature sparse representation-based classification method for motor imagery EEG pattern recognition
M Miao, A Wang, F Liu - Medical & biological engineering & computing, 2017 - Springer
Effective feature extraction and classification methods are of great importance for motor
imagery (MI)-based brain–computer interface (BCI) systems. The common spatial pattern …
imagery (MI)-based brain–computer interface (BCI) systems. The common spatial pattern …
An adaptive multi-domain feature joint optimization framework based on composite kernels and ant colony optimization for motor imagery EEG classification
M Miao, W Zhang, W Hu, R Wang - Biomedical Signal Processing and …, 2020 - Elsevier
Brain computer interface (BCI) is a novel technology that translates human intention into
command to control external device. Common spatial pattern (CSP) algorithm is most …
command to control external device. Common spatial pattern (CSP) algorithm is most …
Application of artificial bee colony algorithm in feature optimization for motor imagery EEG classification
M Miao, A Wang, F Liu - Neural Computing and Applications, 2018 - Springer
Motor imagery (MI) tasks evoke event-related desynchronization (ERD) and synchronization
(ERS); the ERD-/ERS-related features appearing at specific channels are frequency and …
(ERS); the ERD-/ERS-related features appearing at specific channels are frequency and …
Manifold attention-enhanced multi-domain convolutional network for decoding motor imagery intention
B Lu, X Huang, J Chen, R Fu, G Wen - Knowledge-Based Systems, 2024 - Elsevier
Research in brain-computer interface (BCI), particularly in brain intention decoding, has
made significant strides relying on the remarkable capabilities of deep learning (DL) …
made significant strides relying on the remarkable capabilities of deep learning (DL) …
Real-time single channel EEG motor imagery based Brain Computer Interface
J Camacho, V Manian - 2016 World Automation Congress …, 2016 - ieeexplore.ieee.org
This paper presents a motor imagery based Brain Computer Interface (BCI) that uses single
channel EEG signal from the C3 or C4 electrode placed in the motor area of the head. Time …
channel EEG signal from the C3 or C4 electrode placed in the motor area of the head. Time …
Time-frequency optimization for discrimination between imagination of right and left hand movements based on two bipolar electroencephalography channels
To enforce a widespread use of efficient and easy to use brain-computer interfaces (BCIs),
the inter-subject robustness should be increased and the number of electrodes should be …
the inter-subject robustness should be increased and the number of electrodes should be …
TASA: Temporal Attention with Spatial Autoencoder Network for Odor-induced Emotion Classification Using EEG
The olfactory system enables humans to smell different odors, which are closely related to
emotions. The high temporal resolution and non-invasiveness of Electroencephalogram …
emotions. The high temporal resolution and non-invasiveness of Electroencephalogram …