AIMC Topic: Signal Processing, Computer-Assisted

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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...
Humans Electrocardiography Forecasting Machine Learning Signal Processing, Computer-Assisted Algorithms Cardiovascular Diseases Deep Learning
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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...
Deep Learning Ultrasonography Image Processing, Computer-Assisted Animals Microbubbles Phantoms, Imaging Contrast Media Signal Processing, Computer-Assisted Signal-To-Noise Ratio
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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 Adult Male Neural Networks, Computer Middle Aged Signal Processing, Computer-Assisted Aged Machine Learning Adolescent Heart Ventricles Female Photoplethysmography Tachycardia, Supraventricular Young Adult Electrocardiography
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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 Brain-Computer Interfaces Humans 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...
Sleep Stages Neural Networks, Computer Humans Signal Processing, Computer-Assisted Polysomnography
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Deep learning models for segmenting phonocardiogram signals: a comparative study.

PloS one Apr 14, 2025
Cardiac auscultation requires the mechanical vibrations occurring on the body's surface, which carries a range of sound frequencies. These sounds are generated by the movement and pulsation of different cardiac structures as they facilitate blood cir...
Phonocardiography Neural Networks, Computer Humans Deep Learning Algorithms Signal Processing, Computer-Assisted Heart Sounds
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AADNet: Exploring EEG Spatiotemporal Information for Fast and Accurate Orientation and Timbre Detection of Auditory Attention Based on a Cue-Masked Paradigm.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Apr 14, 2025
Auditory attention decoding from electroencephalogram (EEG) could infer to which source the user is attending in noisy environments. Decoding algorithms and experimental paradigm designs are crucial for the development of technology in practical appl...
Algorithms Female Young Adult Auditory Perception Humans Electroencephalography Orientation Cues Signal Processing, Computer-Assisted Adult Acoustic Stimulation Attention Male Deep Learning
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ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

BMC cardiovascular disorders Apr 7, 2025
A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly imp...
Heart Rate Electrocardiography Action Potentials Predictive Value of Tests Signal Processing, Computer-Assisted Arrhythmias, Cardiac Algorithms Reproducibility of Results Diagnosis, Computer-Assisted Humans Machine Learning
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ECG Sensor Design Assessment with Variational Autoencoder-Based Digital Watermarking.

Sensors (Basel, Switzerland) Apr 5, 2025
Designing an ECG sensor circuit requires a comprehensive approach to detect, amplify, filter, and condition the weak electrical signals produced by the heart. To evaluate sensor performance under realistic conditions, diverse ECG signals with embedde...
Humans Electrocardiography Signal Processing, Computer-Assisted Computer Security Autoencoder
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