AIMC Topic: Electroencephalography

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Revisiting Euclidean alignment for transfer learning in EEG-based brain-computer interfaces.

Journal of neural engineering Jun 30, 2025
Due to large intra-subject and inter-subject variabilities of electroencephalogram (EEG) signals, EEG-based brain-computer interfaces (BCIs) usually need subject-specific calibration to tailor the decoding algorithm for each new subject, which is tim...
Electroencephalography Brain-Computer Interfaces Transfer, Psychology Machine Learning Algorithms Humans
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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...
Speech Electroencephalography Imagination Brain-Computer Interfaces Humans Brain
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The class imbalance problem in automatic localization of the epileptogenic zone for epilepsy surgery: a systematic review.

Journal of neural engineering Jun 26, 2025
Accurate localization of the epileptogenic zone (EZ) is crucial for epilepsy surgery, but the class imbalance of epileptogenic vs. non-epileptogenic electrode contacts in intracranial electroencephalography (iEEG) data poses significant challenges fo...
Epilepsy Humans Electrocorticography Machine Learning Electrodes, Implanted Electroencephalography
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A novel dual-branch network for comprehensive spatiotemporal information integration for EEG-based epileptic seizure detection.

PloS one Jun 26, 2025
Epilepsy is a neurological disorder characterized by recurrent seizures caused by abnormal brain activity, which can severely affects people's normal lives. To improve the lives of these patients, it is necessary to develop accurate methods to predic...
Algorithms Deep Learning Electroencephalography Humans Neural Networks, Computer Signal Processing, Computer-Assisted Epilepsy Seizures
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Epilepsy Prediction via Time-Frequency Features and Multi-Scale Hybrid Neural Networks.

Journal of medical systems Jun 25, 2025
The prediction of epileptic seizures heavily depends on the precise embedding and classification of complex, multi-dimensional electroencephalogram (EEG) signals. Due to individual variability and the dynamic non-linear nature of EEG signals, extract...
Neural Networks, Computer Electroencephalography Epilepsy Humans Signal Processing, Computer-Assisted
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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...
Education Deep Learning Electroencephalography Brain-Computer Interfaces Congresses as Topic Datasets as Topic Humans Machine Learning
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Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study.

Journal of neuroengineering and rehabilitation Jun 18, 2025
BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walking ability in stroke patients compared to conventional rehabilitation, but the neural mechanisms remain unclear. This study aims to explore the effec...
Motor Cortex Spectroscopy, Near-Infrared Gait Disorders, Neurologic Humans Treatment Outcome Aged Male Gait Robotics Female Adult Middle Aged Electroencephalography Exercise Therapy Stroke Stroke Rehabilitation
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Test-retest reliability of kinematic and EEG low-beta spectral features in a robot-based arm movement task.

Biomedical physics & engineering express Jun 18, 2025
Low-beta (L, 13-20 Hz) power plays a key role in upper-limb motor control and afferent processing, making it a strong candidate for a neurophysiological biomarker. We investigate the test-retest reliability of Lpower and kinematic features from a rob...
Young Adult Adult Male Robotics Biomechanical Phenomena Movement Female Electroencephalography Arm Reproducibility of Results Humans
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Identifying and predicting EEG microstates with sequence-to-sequence deep learning models for online applications.

Journal of neural engineering Jun 17, 2025
Electroencephalographic (EEG) microstates, as a non-invasive and high-temporal-resolution tool for analyzing time-space features of brain activity, have been validated and applied in various research domains. However, current methods for EEG microsta...
Online Systems Brain Deep Learning Humans Electroencephalography Neural Networks, Computer
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Adaptive weighted dual MAML: Proposing a novel method for the automated diagnosis of partial sleep deprivation.

PloS one Jun 13, 2025
INTRODUCTION: Sleep disorders significantly disrupt normal sleep patterns and pose serious health risks. Traditional diagnostic methods, such as questionnaires and polysomnography, often require extensive time and are susceptible to errors. This high...
Sleep Deprivation Wavelet Analysis Polysomnography Female Adult Humans Algorithms Neural Networks, Computer Male Electroencephalography Signal Processing, Computer-Assisted
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