Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: A review

H Altaheri, G Muhammad, M Alsulaiman… - Neural Computing and …, 2023 - Springer
The brain–computer interface (BCI) is an emerging technology that has the potential to
revolutionize the world, with numerous applications ranging from healthcare to human …

Review of machine learning techniques for EEG based brain computer interface

S Aggarwal, N Chugh - Archives of Computational Methods in …, 2022 - Springer
A brain computer interface (BCI) framework uses computer algorithms to detect mental
activity patterns and manipulate external devices. Because of its simplicity and non …

A comprehensive survey of the Internet of Things (IoT) and AI-based smart healthcare

F Alshehri, G Muhammad - IEEE access, 2020 - ieeexplore.ieee.org
Smart health care is an important aspect of connected living. Health care is one of the basic
pillars of human need, and smart health care is projected to produce several billion dollars …

Deep learning for motor imagery EEG-based classification: A review

A Al-Saegh, SA Dawwd, JM Abdul-Jabbar - Biomedical Signal Processing …, 2021 - Elsevier
Objectives The availability of large and varied Electroencephalogram (EEG) datasets,
rapidly advances and inventions in deep learning techniques, and highly powerful and …

A transformer-based approach combining deep learning network and spatial-temporal information for raw EEG classification

J Xie, J Zhang, J Sun, Z Ma, L Qin, G Li… - … on Neural Systems …, 2022 - ieeexplore.ieee.org
The attention mechanism of the Transformer has the advantage of extracting feature
correlation in the long-sequence data and visualizing the model. As time-series data, the …

Physics-informed attention temporal convolutional network for EEG-based motor imagery classification

H Altaheri, G Muhammad… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
The brain-computer interface (BCI) is a cutting-edge technology that has the potential to
change the world. Electroencephalogram (EEG) motor imagery (MI) signal has been used …

A transfer learning-based CNN and LSTM hybrid deep learning model to classify motor imagery EEG signals

Z Khademi, F Ebrahimi, HM Kordy - Computers in biology and medicine, 2022 - Elsevier
Abstract In the Motor Imagery (MI)-based Brain Computer Interface (BCI), users' intention is
converted into a control signal through processing a specific pattern in brain signals …

Brain-computer interface: Advancement and challenges

MF Mridha, SC Das, MM Kabir, AA Lima, MR Islam… - Sensors, 2021 - mdpi.com
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …

Lightweight and anonymity-preserving user authentication scheme for IoT-based healthcare

M Masud, GS Gaba, K Choudhary… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
Internet of Things (IoT) produces massive heterogeneous data from various applications,
including digital health, smart hospitals, automated pathology labs, and so forth. IoT sensor …

Edge intelligence and Internet of Things in healthcare: A survey

SU Amin, MS Hossain - Ieee Access, 2020 - ieeexplore.ieee.org
With the advent of new technologies and the fast pace of human life, patients today require a
sophisticated and advanced smart healthcare framework that is tailored to suit their …