AIMC Topic: Signal Processing, Computer-Assisted

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Incremental Classification for High-Dimensional EEG Manifold Representation Using Bidirectional Dimensionality Reduction and Prototype Learning.

IEEE journal of biomedical and health informatics Feb 10, 2025
In brain-computer interface (BCI) systems, symmetric positive definite (SPD) manifold within Riemannian space has been frequently utilized to extract spatial features from electroencephalogram (EEG) signals. However, the intrinsic high dimensionality...
Humans Neural Networks, Computer Signal Processing, Computer-Assisted Brain-Computer Interfaces Dimensionality Reduction Adult Principal Component Analysis Electroencephalography Machine Learning Algorithms Brain
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EEG Temporal-Spatial Feature Learning for Automated Selection of Stimulus Parameters in Electroconvulsive Therapy.

IEEE journal of biomedical and health informatics Feb 10, 2025
The risk of adverse effects in Electroconvulsive Therapy (ECT), such as cognitive impairment, can be high if an excessive stimulus is applied to induce the necessary generalized seizure (GS); Conversely, inadequate stimulus results in failure. Recent...
Seizures Signal Processing, Computer-Assisted Electroconvulsive Therapy Male Middle Aged Electroencephalography Female Adult Humans Machine Learning
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Innovative Dual-Decoupling CNN With Layer-Wise Temporal-Spatial Attention for Sensor-Based Human Activity Recognition.

IEEE journal of biomedical and health informatics Feb 10, 2025
Human Activity Recognition (HAR) is essential for monitoring and analyzing human behavior, particularly in health applications such as fall detection and chronic disease management. Traditional methods, even those incorporating attention mechanisms, ...
Humans Neural Networks, Computer Algorithms Signal Processing, Computer-Assisted Monitoring, Ambulatory Human Activities
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A Multimodal Consistency-Based Self-Supervised Contrastive Learning Framework for Automated Sleep Staging in Patients With Disorders of Consciousness.

IEEE journal of biomedical and health informatics Feb 10, 2025
Sleep is a fundamental human activity, and automated sleep staging holds considerable investigational potential. Despite numerous deep learning methods proposed for sleep staging that exhibit notable performance, several challenges remain unresolved,...
Male Deep Learning Electroencephalography Humans Female Adult Sleep Stages Consciousness Disorders Signal Processing, Computer-Assisted Supervised Machine Learning Electrooculography
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Joint Energy-Based Model for Semi-Supervised Respiratory Sound Classification: A Method of Insensitive to Distribution Mismatch.

IEEE journal of biomedical and health informatics Feb 10, 2025
Semi-supervised learning effectively mitigates the lack of labeled data by introducing extensive unlabeled data. Despite achieving success in respiratory sound classification, in practice, it usually takes years to acquire a sufficiently sizeable unl...
Humans COVID-19 Supervised Machine Learning Algorithms Respiratory Sounds SARS-CoV-2 Signal Processing, Computer-Assisted
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EEGConvNeXt: A novel convolutional neural network model for automated detection of Alzheimer's Disease and Frontotemporal Dementia using EEG signals.

Computer methods and programs in biomedicine Feb 8, 2025
BACKGROUND AND OBJECTIVE: Deep learning models have gained widespread adoption in healthcare for accurate diagnosis through the analysis of brain signals. Neurodegenerative disorders like Alzheimer's Disease (AD) and Frontotemporal Dementia (FD) are ...
Signal Processing, Computer-Assisted Alzheimer Disease Frontotemporal Dementia Deep Learning Convolutional Neural Networks Humans Electroencephalography Neural Networks, Computer Algorithms
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DeepReducer: A linear transformer-based model for MEG denoising.

NeuroImage Feb 8, 2025
Measuring event-related magnetic fields (ERFs) in magnetoencephalography (MEG) is crucial for investigating perceptual and cognitive information processing in both neuroscience research and clinical practice. However, the magnitude of the ERF in cort...
Magnetoencephalography Signal Processing, Computer-Assisted Artifacts Signal-To-Noise Ratio Humans Brain Deep Learning
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Explainable AI-driven scalogram analysis and optimized transfer learning for sleep apnea detection with single-lead electrocardiograms.

Computers in biology and medicine Feb 8, 2025
Sleep apnea, a fatal sleep disorder causing repetitive respiratory cessation, requires immediate intervention due to neuropsychological issues. However, existing approaches such as polysomnography, considered the most reliable and accurate test to de...
Polysomnography Humans Deep Learning Algorithms Electrocardiography Databases, Factual Signal Processing, Computer-Assisted Female Sleep Apnea Syndromes Male
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Characterizing drivers of change in intraoperative cerebral saturation using supervised machine learning.

Journal of clinical monitoring and computing Feb 7, 2025
Regional cerebral oxygen saturation (rSO) is used to monitor cerebral perfusion with emerging evidence that optimization of rSO may improve neurological and non-neurological outcomes. To manipulate rSO an understanding of the variables that drive its...
Hemodynamics Machine Learning Monitoring, Intraoperative Algorithms Brain Humans ROC Curve Aged Carbon Dioxide Male Adult Cerebrovascular Circulation Oxygen Female Oxygen Saturation Middle Aged Oximetry Signal Processing, Computer-Assisted Spectroscopy, Near-Infrared Supervised Machine Learning Reproducibility of Results
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A two-branch framework for blood pressure estimation using photoplethysmography signals with deep learning and clinical prior physiological knowledge.

Physiological measurement Feb 7, 2025
This paper presents a novel dual-branch framework for estimating blood pressure (BP) using photoplethysmography (PPG) signals. The method combines deep learning with clinical prior knowledge and models different time periods (morning, afternoon, and ...
Photoplethysmography Blood Pressure Determination Blood Pressure Signal Processing, Computer-Assisted Adult Male Deep Learning Humans Female
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