AIMC Topic: Brain-Computer Interfaces

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Multi-Scale Pyramid Squeeze Attention Similarity Optimization Classification Neural Network for ERP Detection.

Neural networks : the official journal of the International Neural Network Society
Event-related potentials (ERPs) can reveal brain activity elicited by external stimuli. Innovative methods to decode ERPs could enhance the accuracy of brain-computer interface (BCI) technology and promote the understanding of cognitive processes. Th...

Multiscale Spatial-Temporal Feature Fusion Neural Network for Motor Imagery Brain-Computer Interfaces.

IEEE journal of biomedical and health informatics
Motor imagery, one of the main brain-computer interface (BCI) paradigms, has been extensively utilized in numerous BCI applications, such as the interaction between disabled people and external devices. Precise decoding, one of the most significant a...

MFRC-Net: Multi-Scale Feature Residual Convolutional Neural Network for Motor Imagery Decoding.

IEEE journal of biomedical and health informatics
Motor imagery (MI) decoding is the basis of external device control via electroencephalogram (EEG). However, the majority of studies prioritize enhancing the accuracy of decoding methods, often overlooking the magnitude and computational resource dem...

A hybrid network using transformer with modified locally linear embedding and sliding window convolution for EEG decoding.

Journal of neural engineering
. Brain-computer interface(BCI) is leveraged by artificial intelligence in EEG signal decoding, which makes it possible to become a new means of human-machine interaction. However, the performance of current EEG decoding methods is still insufficient...

Enhancing the performance of SSVEP-based BCIs by combining task-related component analysis and deep neural network.

Scientific reports
Steady-State Visually Evoked Potential (SSVEP) signals can be decoded by either a traditional machine learning algorithm or a deep learning network. Combining the two methods is expected to enhance the performance of an SSVEP-based brain-computer int...

Imagining alternative futures with augmentative and alternative communication: a manifesto.

Medical humanities
This manifesto seeks to challenge dominant narratives about the future of augmentative and alternative communication (AAC). Current predictions are mainly driven by technological developments-technologies usually being developed for different markets...

A Bibliometric Review of Brain-Computer Interfaces in Motor Imagery and Steady-State Visually Evoked Potentials for Applications in Rehabilitation and Robotics.

Sensors (Basel, Switzerland)
In this paper, a bibliometric review is conducted on brain-computer interfaces (BCI) in non-invasive paradigms like motor imagery (MI) and steady-state visually evoked potentials (SSVEP) for applications in rehabilitation and robotics. An exploratory...

EEG-based emotion recognition using multi-scale dynamic CNN and gated transformer.

Scientific reports
Emotions play a crucial role in human thoughts, cognitive processes, and decision-making. EEG has become a widely utilized tool in emotion recognition due to its high temporal resolution, real-time monitoring capabilities, portability, and cost-effec...

Performance investigation of MVMD-MSI algorithm in frequency recognition for SSVEP-based brain-computer interface and its application in robotic arm control.

Medical & biological engineering & computing
This study focuses on improving the performance of steady-state visual evoked potential (SSVEP) in brain-computer interfaces (BCIs) for robotic control systems. The challenge lies in effectively reducing the impact of artifacts on raw data to enhance...

Emotion recognition using multi-scale EEG features through graph convolutional attention network.

Neural networks : the official journal of the International Neural Network Society
Emotion recognition via electroencephalogram (EEG) signals holds significant promise across various domains, including the detection of emotions in patients with consciousness disorders, assisting in the diagnosis of depression, and assessing cogniti...