A survey on the metaverse: The state-of-the-art, technologies, applications, and challenges
H Wang, H Ning, Y Lin, W Wang… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
In recent years, the concept of the Metaverse has attracted considerable attention. This
article provides a comprehensive overview of the Metaverse. First, the development status of …
article provides a comprehensive overview of the Metaverse. First, the development status of …
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 …
activity patterns and manipulate external devices. Because of its simplicity and non …
Adaptive transfer learning-based multiscale feature fused deep convolutional neural network for EEG MI multiclassification in brain–computer interface
AM Roy - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
Abstract Objective. Deep learning (DL)-based brain–computer interface (BCI) in motor
imagery (MI) has emerged as a powerful method for establishing direct communication …
imagery (MI) has emerged as a powerful method for establishing direct communication …
Past, present, and future of EEG-based BCI applications
K Värbu, N Muhammad, Y Muhammad - Sensors, 2022 - mdpi.com
An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that
provides a pathway between the brain and external devices by interpreting EEG. EEG …
provides a pathway between the brain and external devices by interpreting EEG. EEG …
Interface, interaction, and intelligence in generalized brain–computer interfaces
A brain–computer interface (BCI) establishes a direct communication channel between a
brain and an external device. With recent advances in neurotechnology and artificial …
brain and an external device. With recent advances in neurotechnology and artificial …
Current status, challenges, and possible solutions of EEG-based brain-computer interface: a comprehensive review
Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices
through the utilization of brain waves. It is worth noting that the application of BCI is not …
through the utilization of brain waves. It is worth noting that the application of BCI is not …
Brain-computer interface: Advancement and challenges
Brain-Computer Interface (BCI) is an advanced and multidisciplinary active research domain
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
based on neuroscience, signal processing, biomedical sensors, hardware, etc. Since the …
Uncovering the structure of clinical EEG signals with self-supervised learning
Objective. Supervised learning paradigms are often limited by the amount of labeled data
that is available. This phenomenon is particularly problematic in clinically-relevant data …
that is available. This phenomenon is particularly problematic in clinically-relevant data …
An efficient multi-scale CNN model with intrinsic feature integration for motor imagery EEG subject classification in brain-machine interfaces
AM Roy - Biomedical Signal Processing and Control, 2022 - Elsevier
Objective Electroencephalogram (EEG) based motor imagery (MI) classification is an
important aspect in brain-machine interfaces (BMIs) which bridges between neural system …
important aspect in brain-machine interfaces (BMIs) which bridges between neural system …
An efficient and robust phonocardiography (pcg)-based valvular heart diseases (vhd) detection framework using vision transformer (vit)
Background and objectives: Valvular heart diseases (VHDs) are one of the dominant causes
of cardiovascular abnormalities that have been associated with high mortality rates globally …
of cardiovascular abnormalities that have been associated with high mortality rates globally …