AIMC Topic: Brain-Computer Interfaces

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Speech imagery brain-computer interfaces: a systematic literature review.

Journal of neural engineering Jun 26, 2025
Speech Imagery (SI) refers to the mental experience of hearing speech and may be the core of verbal thinking for people who undergo internal monologues. It belongs to the set of possible mental imagery states that produce kinesthetic experiences whos...
Electroencephalography Brain-Computer Interfaces Imagination Humans Brain Speech
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Learning from small datasets-review of workshop 6 of the 10th International BCI Meeting 2023.

Journal of neural engineering Jun 24, 2025
In a brain-computer interface (BCI), a primary objective is to reduce calibration time by recording as few as possible novel data points to (re-)train decoder models.Minimizing the calibration can be crucial for enhancing the usability of a BCI appli...
Brain-Computer Interfaces Congresses as Topic Education Deep Learning Electroencephalography Datasets as Topic Humans Machine Learning
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POC-CSP: a novel parameterised and orthogonally-constrained neural network layer for learning common spatial patterns (CSP) in EEG signals.

Journal of neural engineering Jun 11, 2025
. Common spatial patterns (CSPs) has been established as a powerful feature extraction method in EEG signal processing with machine learning, but it has shortcomings including sensitivity to noise and rigidity in the value of the weights. Our goal wa...
Male Electroencephalography Brain-Computer Interfaces Neural Networks, Computer Machine Learning Adult Imagination Humans
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Virtual Electroencephalogram Acquisition: A Review on Electroencephalogram Generative Methods.

Sensors (Basel, Switzerland) May 18, 2025
Driven by the remarkable capabilities of machine learning, brain-computer interfaces (BCIs) are carving out an ever-expanding range of applications across a multitude of diverse fields. Notably, electroencephalogram (EEG) signals have risen to promin...
Machine Learning Algorithms Brain Humans Neural Networks, Computer Brain-Computer Interfaces Electroencephalography Signal Processing, Computer-Assisted
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Unsupervised Domain Adaptation With Synchronized Self-Training for Cross- Domain Motor Imagery Recognition.

IEEE journal of biomedical and health informatics May 6, 2025
Robust decoding performance is essential for the practical deployment of brain-computer interface (BCI) systems. Existing EEG decoding models often rely on large amounts of annotated data collected through specific experimental setups, which fail to ...
Humans Algorithms Female Young Adult Adult Male Brain-Computer Interfaces Unsupervised Machine Learning Imagination Electroencephalography Signal Processing, Computer-Assisted
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A Novel 3D Approach with a CNN and Swin Transformer for Decoding EEG-Based Motor Imagery Classification.

Sensors (Basel, Switzerland) May 5, 2025
Motor imagery (MI) is a crucial research field within the brain-computer interface (BCI) domain. It enables patients with muscle or neural damage to control external devices and achieve movement functions by simply imagining bodily motions. Despite t...
Signal Processing, Computer-Assisted Brain-Computer Interfaces Signal-To-Noise Ratio Movement Imagination Algorithms Deep Learning Electroencephalography Humans Neural Networks, Computer
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Convolutional Dynamically Convergent Differential Neural Network for Brain Signal Classification.

IEEE transactions on neural networks and learning systems May 2, 2025
The brain signal classification is the basis for the implementation of brain-computer interfaces (BCIs). However, most existing brain signal classification methods are based on signal processing technology, which require a significant amount of manua...
Neural Networks, Computer Algorithms Brain Electroencephalography Humans Signal Processing, Computer-Assisted Brain-Computer Interfaces
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Enhanced Brain Functional Interaction Following BCI-Guided Supernumerary Robotic Finger Training Based on Sixth-Finger Motor Imagery.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 29, 2025
Supernumerary robotic finger (SRF) has shown unique advantages in the field of motor augmentation and rehabilitation, while the development of brain computer interface (BCI) technology has provided the possibility for direct control of SRF. However, ...
Imagination Female Male Brain-Computer Interfaces Young Adult Humans Fingers Magnetic Resonance Imaging Brain Adult Motor Cortex Brain Mapping Neuronal Plasticity Robotics Psychomotor Performance
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SMANet: A Model Combining SincNet, Multi-Branch Spatial-Temporal CNN, and Attention Mechanism for Motor Imagery BCI.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 29, 2025
Building a brain-computer interface (BCI) based on motor imagery (MI) requires accurately decoding MI tasks, which poses a significant challenge due to individual discrepancy among subjects and low signal-to-noise ratio of EEG signals. We propose an ...
Humans Signal-To-Noise Ratio Neural Networks, Computer Movement Deep Learning Algorithms Attention Electroencephalography Imagination Adult Brain-Computer Interfaces Signal Processing, Computer-Assisted Male
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Advancing Prosthetic Hand Capabilities Through Biomimicry and Neural Interfaces.

Neurorehabilitation and neural repair Apr 24, 2025
Background and ObjectivesProsthetic hand development is undergoing a transformative phase, blending biomimicry and neural interface technologies to redefine functionality and sensory feedback. This article explores the symbiotic relationship between ...
Artificial Limbs Humans Brain-Computer Interfaces Prosthesis Design Hand Biomimetics
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