AIMC Topic: Signal Processing, Computer-Assisted

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AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition.

IEEE transactions on cybernetics Apr 23, 2025
The underlying time-variant and subject-specific brain dynamics lead to inconsistent distributions in electroencephalogram (EEG) topology and representations within and between individuals. However, current works primarily align the distributions of ...
Databases, Factual Attention Humans Brain Emotions Electroencephalography Neural Networks, Computer Signal Processing, Computer-Assisted Algorithms
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Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.

IEEE transactions on cybernetics Apr 23, 2025
The neural activity patterns of localized brain regions are crucial for recognizing brain intentions. However, existing electroencephalogram (EEG) decoding models, especially those based on deep learning, predominantly focus on global spatial feature...
Brain Female Young Adult Adult Male Deep Learning Humans Neural Networks, Computer Intention Imagination Electroencephalography Signal Processing, Computer-Assisted
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HATNet: EEG-Based Hybrid Attention Transfer Learning Network for Train Driver State Detection.

IEEE transactions on cybernetics Apr 23, 2025
Electroencephalography (EEG) is widely utilized for train driver state detection due to its high accuracy and low latency. However, existing methods for driver status detection rarely use the rich physiological information in EEG to improve detection...
Automobile Driving Signal Processing, Computer-Assisted Attention Neural Networks, Computer Machine Learning Algorithms Adult Male Electroencephalography Humans
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Enhancing motor imagery EEG classification with a Riemannian geometry-based spatial filtering (RSF) method.

Neural networks : the official journal of the International Neural Network Society Apr 22, 2025
Motor imagery (MI) refers to the mental simulation of movements without physical execution, and it can be captured using electroencephalography (EEG). This area has garnered significant research interest due to its substantial potential in brain-comp...
Signal-To-Noise Ratio Movement Humans Imagination Algorithms Brain Electroencephalography Signal Processing, Computer-Assisted Brain-Computer Interfaces
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FADE: Forecasting for anomaly detection on ECG.

Computer methods and programs in biomedicine Apr 22, 2025
BACKGROUND AND OBJECTIVE: Cardiovascular diseases, a leading cause of noncommunicable disease-related deaths, require early and accurate detection to improve patient outcomes. Taking advantage of advances in machine learning and deep learning, multip...
Machine Learning Algorithms Forecasting Humans Signal Processing, Computer-Assisted Cardiovascular Diseases Deep Learning Electrocardiography
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Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Apr 22, 2025
Resolving arterial flows is essential for understanding cardiovascular pathologies, improving diagnosis, and monitoring patient condition. Ultrasound contrast imaging uses microbubbles to enhance the scattering of the blood pool, allowing for real-ti...
Phantoms, Imaging Ultrasonography Image Processing, Computer-Assisted Contrast Media Animals Signal Processing, Computer-Assisted Signal-To-Noise Ratio Deep Learning Microbubbles
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Enhanced convolutional neural network accelerators with memory optimization for routing applications.

PloS one Apr 21, 2025
Currently, Convolutional Neural Networks (CNN) accelerators find application in various digital domains, each highlighting memory utilization as a significant concern leading to system degradation. In response, our present work focuses on optimizing ...
Neural Networks, Computer Convolutional Neural Networks Algorithms Signal Processing, Computer-Assisted
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Machine-learning guided differentiation between photoplethysmography waveforms of supraventricular and ventricular origin.

Computer methods and programs in biomedicine Apr 20, 2025
BACKGROUND: It is unclear, whether photoplethysmography (PPG) waveforms from wearable devices can differentiate between supraventricular and ventricular arrhythmias. We assessed, whether a neural network-based classifier can distinguish the origin of...
Humans Neural Networks, Computer Male Heart Ventricles Middle Aged Tachycardia, Supraventricular Aged Adolescent Young Adult Machine Learning Photoplethysmography Adult Female Electrocardiography Signal Processing, Computer-Assisted
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Multi-scale convolutional transformer network for motor imagery brain-computer interface.

Scientific reports Apr 15, 2025
Brain-computer interface (BCI) systems allow users to communicate with external devices by translating neural signals into real-time commands. Convolutional neural networks (CNNs) have been effectively utilized for decoding motor imagery electroencep...
Neural Networks, Computer Brain Electroencephalography Signal Processing, Computer-Assisted Humans Brain-Computer Interfaces Imagination
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Towards interpretable sleep stage classification with a multi-stream fusion network.

BMC medical informatics and decision making Apr 14, 2025
Sleep stage classification is a significant measure in assessing sleep quality and diagnosing sleep disorders. Many researchers have investigated automatic sleep stage classification methods and achieved promising results. However, these methods igno...
Signal Processing, Computer-Assisted Polysomnography Sleep Stages Humans Neural Networks, Computer
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