AIMC Topic: Electroencephalography

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Multi-Modal Sleep Stage Classification With Two-Stream Encoder-Decoder.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jan 1, 2024
Sleep staging serves as a fundamental assessment for sleep quality measurement and sleep disorder diagnosis. Although current deep learning approaches have successfully integrated multimodal sleep signals, enhancing the accuracy of automatic sleep st...
Humans Neural Networks, Computer Electrooculography Sleep Stages Male Young Adult Deep Learning Signal Processing, Computer-Assisted Adult Algorithms Polysomnography Female Electroencephalography
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[Safety of robot-assisted implantation of deep electrodes for invasive stereo-EEG monitoring].

Zhurnal voprosy neirokhirurgii imeni N. N. Burdenko Jan 1, 2024
UNLABELLED: Robot-assisted implantation of deep electrodes for stereo-EEG monitoring has become popular in recent years in patients with drug-resistant epilepsy. However, there are still few data on safety of this technique.
Humans Retrospective Studies Stereotaxic Techniques Drug Resistant Epilepsy Electrodes, Implanted Robotics Electroencephalography
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BiTCAN: A emotion recognition network based on saliency in brain cognition.

Mathematical biosciences and engineering : MBE Dec 5, 2023
In recent years, with the continuous development of artificial intelligence and brain-computer interfaces, emotion recognition based on electroencephalogram (EEG) signals has become a prosperous research direction. Due to saliency in brain cognition,...
Algorithms Brain Artificial Intelligence Electroencephalography Cognition Emotions
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Research on Brain Signals Classification Based on Deep Learning.

Studies in health technology and informatics Nov 23, 2023
With the continuous expansion of brain-computer communication, the precise identification of brain signals has become an essential task for brain-computer equipment. However, existing classification methods are primarily concentrated on the extractio...
Deep Learning Electroencephalography Algorithms Brain Humans Neural Networks, Computer
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Perspective of Signal Processing-Based on Brain-Computer Interfaces Using Machine Learning Methods.

Studies in health technology and informatics Nov 23, 2023
The application of artificial intelligence (AI) algorithms is an indispensable portion of developing brain-computer interfaces (BCI). With the continuous development of AI concepts and related technologies. AI algorithms such as neural networks play ...
Brain-Computer Interfaces Artificial Intelligence Machine Learning Electroencephalography Signal Processing, Computer-Assisted Algorithms
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AGL-Net: An Efficient Neural Network for EEG-Based Driver Fatigue Detection.

Journal of integrative neuroscience Oct 23, 2023
BACKGROUND: In recent years, road traffic safety has become a prominent issue due to the worldwide proliferation of vehicles on roads. The challenge of driver fatigue detection involves balancing the efficiency and accuracy of the detection process. ...
Emotions Linear Models Neural Networks, Computer Humans Electroencephalography China
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A regression model combined convolutional neural network and recurrent neural network for electroencephalogram-based cross-subject fatigue detection.

The Review of scientific instruments Sep 1, 2023
Fatigue, one of the most important factors affecting road safety, has attracted many researchers' attention. Most existing fatigue detection methods are based on feature engineering and classification models. The feature engineering is greatly influe...
Neural Networks, Computer Electroencephalography Calibration
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A convolutional neural network-based decision support system for neonatal quiet sleep detection.

Mathematical biosciences and engineering : MBE Aug 29, 2023
Sleep plays an important role in neonatal brain and physical development, making its detection and characterization important for assessing early-stage development. In this study, we propose an automatic and computationally efficient algorithm to det...
Infant, Newborn Sleep Humans China Sleep Stages Neural Networks, Computer Child Algorithms Electroencephalography
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Automated Interpretation of Clinical Electroencephalograms Using Artificial Intelligence.

JAMA neurology Aug 1, 2023
IMPORTANCE: Electroencephalograms (EEGs) are a fundamental evaluation in neurology but require special expertise unavailable in many regions of the world. Artificial intelligence (AI) has a potential for addressing these unmet needs. Previous AI mode...
Male Electroencephalography Epilepsy Reproducibility of Results Adult Neural Networks, Computer Artificial Intelligence Humans
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Magnetoencephalogram-based brain-computer interface for hand-gesture decoding using deep learning.

Cerebral cortex (New York, N.Y. : 1991) Jul 5, 2023
Advancements in deep learning algorithms over the past decade have led to extensive developments in brain-computer interfaces (BCI). A promising imaging modality for BCI is magnetoencephalography (MEG), which is a non-invasive functional imaging tech...
Electroencephalography Deep Learning Humans Brain-Computer Interfaces Magnetoencephalography Gestures Algorithms
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