AIMC Topic: Signal Processing, Computer-Assisted
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Entropy-driven deep learning framework for epilepsy detection using electro encephalogram signals.
Neuroscience
May 5, 2025
Epilepsy is one of the most frequently occurring neurological disorders that require early and accurate detection. This paper introduces a novel approach for the automatic identification of epilepsy in EEG signals by incorporating advanced entropy-ba...
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...
Multi-modal signal integration for enhanced sleep stage classification: Leveraging EOG and 2-channel EEG data with advanced feature extraction.
Artificial intelligence in medicine
May 2, 2025
This paper introduces an innovative approach to sleep stage classification, leveraging a multi-modal signal integration framework encompassing Electrooculography (EOG) and two-channel electroencephalography (EEG) data. We explore the utility of vario...
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...
Balancing privacy and health integrity: A novel framework for ECG signal analysis in immersive environments.
Computers in biology and medicine
May 1, 2025
The widespread use of immersive technologies such as Virtual Reality, Mixed Reality, and Augmented Reality has led to the continuous collection and streaming of vast amounts of sensitive biometric data. Among the biometric signals collected, ECG (ele...
TasteNet: A novel deep learning approach for EEG-based basic taste perception recognition using CEEMDAN domain entropy features.
Journal of neuroscience methods
Apr 30, 2025
BACKGROUND: Taste perception is the process by which the gustatory system detects and interprets chemical stimuli from food and beverages, involving activation of taste receptors on the tongue. Analyzing taste perception is essential for understandin...
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 ...
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
Apr 24, 2025
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
Apr 24, 2025
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
Apr 23, 2025
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...
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