Deep learning techniques for classification of electroencephalogram (EEG) motor imagery (MI) signals: A review
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 …
revolutionize the world, with numerous applications ranging from healthcare to human …
EEG-based brain-computer interfaces using motor-imagery: Techniques and challenges
Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly those
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …
using motor-imagery (MI) data, have the potential to become groundbreaking technologies …
A review of user training methods in brain computer interfaces based on mental tasks
Mental-tasks based brain–computer interfaces (MT-BCIs) allow their users to interact with an
external device solely by using brain signals produced through mental tasks. While MT-BCIs …
external device solely by using brain signals produced through mental tasks. While MT-BCIs …
MOABB: trustworthy algorithm benchmarking for BCIs
V Jayaram, A Barachant - Journal of neural engineering, 2018 - iopscience.iop.org
Objective. Brain–computer interface (BCI) algorithm development has long been hampered
by two major issues: small sample sets and a lack of reproducibility. We offer a solution to …
by two major issues: small sample sets and a lack of reproducibility. We offer a solution to …
Towards correlation-based time window selection method for motor imagery BCIs
The start of the cue is often used to initiate the feature window used to control motor imagery
(MI)-based brain-computer interface (BCI) systems. However, the time latency during an MI …
(MI)-based brain-computer interface (BCI) systems. However, the time latency during an MI …
Electroencephalography
GR Müller-Putz - Handbook of clinical neurology, 2020 - Elsevier
The electroencephalogram (EEG) was invented almost 100 years ago and is still a method
of choice for many research questions, even applications—from functional brain imaging in …
of choice for many research questions, even applications—from functional brain imaging in …
Heading for new shores! Overcoming pitfalls in BCI design
Research in brain-computer interfaces has achieved impressive progress towards
implementing assistive technologies for restoration or substitution of lost motor capabilities …
implementing assistive technologies for restoration or substitution of lost motor capabilities …
Riemannian geometric and ensemble learning for decoding cross-session motor imagery electroencephalography signals
Objective. Brain–computer interfaces (BCIs) enable a direct communication pathway
between the human brain and external devices, without relying on the traditional peripheral …
between the human brain and external devices, without relying on the traditional peripheral …
Eeg-based mental tasks recognition via a deep learning-driven anomaly detector
This paper introduces an unsupervised deep learning-driven scheme for mental tasks'
recognition using EEG signals. To this end, the Multichannel Wiener filter was first applied to …
recognition using EEG signals. To this end, the Multichannel Wiener filter was first applied to …
Current Trends, Challenges, and Future Research Directions of Hybrid and Deep Learning Techniques for Motor Imagery Brain–Computer Interface
E Lionakis, K Karampidis, G Papadourakis - … Technologies and Interaction, 2023 - mdpi.com
The field of brain–computer interface (BCI) enables us to establish a pathway between the
human brain and computers, with applications in the medical and nonmedical field. Brain …
human brain and computers, with applications in the medical and nonmedical field. Brain …