A CNN-based modular classification scheme for motor imagery using a novel EEG sampling protocol suitable for IoT healthcare systems
MI Chacon-Murguia, E Rivas-Posada - Neural Computing and …, 2023 - Springer
The implementation of brain-computer interfaces (BCI) for real-time has become a
paramount technology. Implementation of real-time BCI systems requires of methodologies …
paramount technology. Implementation of real-time BCI systems requires of methodologies …
Deep neural networks for real time Motor-Imagery EEG signal classification
A Selim - 2023 - aru.figshare.com
The aim of this research is to develop a high-performance Motor Imagery (MI) classifier
capable of using short signal intervals (0.8 s) in an effort to move towards real-time …
capable of using short signal intervals (0.8 s) in an effort to move towards real-time …
Classification methods in EEG based motor imagery BCI systems
The structure and functioning of the human brain has always attracted the attention of
scientists. In the past 10-20 years, one of the popular areas of study related to the human …
scientists. In the past 10-20 years, one of the popular areas of study related to the human …
A Comprehensive Approach for Enhancing Motor Imagery EEG Classification in BCI's
Electroencephalography (EEG) based on motor imagery has become a potential modality
for brain-computer interface (BCI) systems, allowing users to control external devices by …
for brain-computer interface (BCI) systems, allowing users to control external devices by …
Image-based motor imagery EEG classification using convolutional neural network
Motor Imagery (MI) based Brain Computer Interface (BCI) has clinical applications such as
rehabilitation or communication for patients who have lost motor functions. Accurate …
rehabilitation or communication for patients who have lost motor functions. Accurate …
Classification of Motor Imagery EEG signals using high resolution time-frequency representations and convolutional neural network
V Srimadumathi, MR Reddy - Biomedical Physics & Engineering …, 2024 - iopscience.iop.org
Abstract A Motor Imagery (MI) based Brain Computer Interface (BCI) system aims to provide
neuro-rehabilitation for the motor disabled people and patients with brain injuries (eg, stroke …
neuro-rehabilitation for the motor disabled people and patients with brain injuries (eg, stroke …
Normalized deep learning algorithms based information aggregation functions to classify motor imagery EEG signal
Recently, the discipline of Brain-Computer-Interface (BCI) has attracted attention to
exploiting Electroencephalograph (EEG) mental activities such as Motor Imagery (MI) …
exploiting Electroencephalograph (EEG) mental activities such as Motor Imagery (MI) …
Round cosine transform based feature extraction of motor imagery EEG signals
RB Braga, CD Lopes, T Becker - World Congress on Medical Physics and …, 2019 - Springer
Abstract Brain Computer Interfaces (BCIs) are systems with great potential for the
rehabilitation of people with severe motor injuries. By analyzing a subject's brain waves, it is …
rehabilitation of people with severe motor injuries. By analyzing a subject's brain waves, it is …
Classification Procedure for Motor Imagery EEG Data
E Sales Barros, N Neto - … : 12th International Conference, AC 2018, Held as …, 2018 - Springer
Brain computer interface establishes a new model of communication, whereby it is possible
to communicate using only cerebral signals, that can be obtained from different kind of …
to communicate using only cerebral signals, that can be obtained from different kind of …
An approach to EEG based BCI for motor imagery using time-frequency representation and CNN
Ž Rohutná, R Vargic - 2022 29th International Conference on …, 2022 - ieeexplore.ieee.org
In this contribution, we use electroencephalography for brain-computer interface and focus
on two-class recognition of motor imagery data. We present a method with various …
on two-class recognition of motor imagery data. We present a method with various …