Brain–computer interface: trend, challenges, and threats
Abstract Brain–computer interface (BCI), an emerging technology that facilitates
communication between brain and computer, has attracted a great deal of research in recent …
communication between brain and computer, has attracted a great deal of research in recent …
A systematic literature review on machine learning algorithms for human status detection
Human status detection (HSD) is important to understand the status of users when
interacting with various systems under different conditions. Recently, although various …
interacting with various systems under different conditions. Recently, although various …
DualDomain-AttenNet: Synergizing time–frequency analysis and attention mechanisms for Motor Imagery BCI enhancement
CL Liu, PT Huang - Advanced Engineering Informatics, 2024 - Elsevier
Abstract This paper introduces DualDomain-AttenNet, a novel deep learning model for brain–
computer interfaces (BCI) based on electroencephalography (EEG) data, focusing on …
computer interfaces (BCI) based on electroencephalography (EEG) data, focusing on …
Deep convolutional neural network for EEG-based motor decoding
Brain–machine interfaces (BMIs) have been applied as a pattern recognition system for
neuromodulation and neurorehabilitation. Decoding brain signals (eg, EEG) with high …
neuromodulation and neurorehabilitation. Decoding brain signals (eg, EEG) with high …
BIO‐inspired fuzzy inference system—For physiological signal analysis
When a person's neuromuscular system is affected by an injury or disease, Activities‐for‐
Daily‐Living (ADL), such as gripping, turning, and walking, are impaired …
Daily‐Living (ADL), such as gripping, turning, and walking, are impaired …
Cognition-Supervised Saliency Detection: Contrasting EEG Signals and Visual Stimuli
J Ma, T Ruotsalo - Proceedings of the 32nd ACM International …, 2024 - dl.acm.org
Understanding human assessment of semantically salient parts of multimedia content is
crucial for developing human-centric applications, such as annotation tools, search and …
crucial for developing human-centric applications, such as annotation tools, search and …
Large scale investigation of the effect of gender on mu rhythm suppression in motor imagery brain-computer interfaces
The utmost issue in Motor Imagery Brain-Computer Interfaces (MI-BCI) is the BCI poor
performance known as 'BCI inefficiency'. Although past research has attempted to find a …
performance known as 'BCI inefficiency'. Although past research has attempted to find a …
[HTML][HTML] Machine learning techniques for electroencephalogram based brain-computer interface: A systematic literature review
R Dhiman - Measurement: Sensors, 2023 - Elsevier
Brain-computer interface systems with Electroencephalogram (EEG), especially those use
motor-imagery (MI) signals, have demonstrated the ability to control electromechanical …
motor-imagery (MI) signals, have demonstrated the ability to control electromechanical …
Efficient predefined time adaptive neural network for motor execution EEG signal classification based brain-computer interaction
Nowadays, Electroencephalogram (EEG) devices that do not require invasive procedures
get more attraction. Brain-Computer Interface (BCI) systems use EEG analysis to identify …
get more attraction. Brain-Computer Interface (BCI) systems use EEG analysis to identify …
A multimodal framework based on deep belief network for human locomotion intent prediction
J Li, J Zhang, K Li, J Cao, H Li - Biomedical Engineering Letters, 2024 - Springer
Accurate prediction of human locomotion intent benefits the seamless switching of lower
limb exoskeleton controllers in different terrains to assist humans in walking safely. In this …
limb exoskeleton controllers in different terrains to assist humans in walking safely. In this …