AIMC Topic: Signal Processing, Computer-Assisted

Clear Filters Showing 151 to 160 of 2081 articles

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
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 ...

Unveiling fetal heart health: harnessing auto-metric graph neural networks and Hazelnut tree search for ECG-based arrhythmia detection.

Computer methods in biomechanics and biomedical engineering
Fetal electrocardiogram (ECG) provides a non-invasive means to assess fetal heart health, but isolating the fetal signal from the dominant maternal ECG remains challenging. This study introduces the FHH-AMGNN-HTSOA-ECG-AD method for enhanced fetal ar...

Enhanced EEG-based Alzheimer's disease detection using synchrosqueezing transform and deep transfer learning.

Neuroscience
The most prevalent type of dementia and a progressive neurodegenerative disease, Alzheimer's disease has a major influence on day-to-day functioning due to memory loss, cognitive decline, and behavioral problems. By using synchrosqueezing representat...

Data-driven sleep structure deciphering based on cardiorespiratory signals.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Cardiorespiratory signals provide a novel perspective for understanding sleep structure through the physiological mechanism of cardiopulmonary coupling. This mechanism divides the coupling spectrum into high-frequency (HF) a...

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

IEEE transactions on cybernetics
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 ...

Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.

IEEE transactions on cybernetics
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...

HATNet: EEG-Based Hybrid Attention Transfer Learning Network for Train Driver State Detection.

IEEE transactions on cybernetics
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...

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
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...

FADE: Forecasting for anomaly detection on ECG.

Computer methods and programs in biomedicine
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...

Waveform-Specific Performance of Deep Learning-Based Super-Resolution for Ultrasound Contrast Imaging.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
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...