Improving EEG-based driver distraction classification using brain connectivity estimators
This paper discusses a novel approach to an EEG (electroencephalogram)-based driver
distraction classification by using brain connectivity estimators as features. Ten healthy …
distraction classification by using brain connectivity estimators as features. Ten healthy …
High accuracy decoding of motor imagery directions from EEG-based brain computer interface using filter bank spatially regularised common spatial pattern method
One of the important requirements of a practical Brain Computer Interface (BCI) system is the
ability to establish multiple control commands corresponding to different kinematics of motor …
ability to establish multiple control commands corresponding to different kinematics of motor …
The Multiple Frequency Conversion Sinusoidal Chaotic Neural Network and Its Application
Z Hu, Z Guo, G Wang, L Wang, X Zhao, Y Zhang - Fractal and Fractional, 2023 - mdpi.com
Aiming at the problem that the global search performance of a transiently chaotic neural
network is not ideal, a multiple frequency conversion sinusoidal chaotic neural network …
network is not ideal, a multiple frequency conversion sinusoidal chaotic neural network …
Direction decoding of imagined hand movements using subject-specific features from parietal EEG
Objective. Research on the decoding of brain signals to control external devices is rapidly
emerging due to its versatile potential applications, including neuroprosthetic control and …
emerging due to its versatile potential applications, including neuroprosthetic control and …
FSTA-Net: Motor Imagery EEG Decoding Based on Frequency-Spatial-Time Features
Decoding electroencephalography (EEG) signals based on motor imagery (MI) is vital in
rehabilitation and motor-assisted instrumentation. As an essential step in decoding, feature …
rehabilitation and motor-assisted instrumentation. As an essential step in decoding, feature …
A spatio-temporal interactive attention network for motor imagery eeg decoding
Brain-computer interface (BCI) technology can link direct communication paths between
human brain and external devices, where tasks of motor imagery (MI) electroencephalogram …
human brain and external devices, where tasks of motor imagery (MI) electroencephalogram …
Single Channel-based Motor Imagery Classification using Fisher's Ratio and Pearson Correlation
Motor imagery-based BCI systems have been promising and gaining popularity in
rehabilitation and Activities of daily life (ADL). Despite this, the technology is still emerging …
rehabilitation and Activities of daily life (ADL). Despite this, the technology is still emerging …
A Phase-based EEG Epoch Selection Method for Decoding Bi-directional Hand Movement Imagination in Stroke Patients
S Gangadharan, AP Vinod… - 2023 45th Annual …, 2023 - ieeexplore.ieee.org
Electroencephalogram (EEG) based non-invasive Brain Computer Interface (BCI) system is
gaining significant attention as a promising solution for stroke rehabilitation. Accurate …
gaining significant attention as a promising solution for stroke rehabilitation. Accurate …
Iterative outlier removal clustering based time-frequency-spatial feature selection for binary EEG motor imagery decoding
Electroencephalography (EEG)-based motor imagery (MI) brain-computer interface (BCI) is
a bridge in the instruments of rehabilitation and motor assistance field to control external …
a bridge in the instruments of rehabilitation and motor assistance field to control external …