AIMC Topic: Arrhythmias, Cardiac

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Reliability and validity of a novel single-lead portable electrocardiogram device for pregnant women: a comparative study.

BMC medical informatics and decision making Mar 3, 2025
BACKGROUND: WenXinWuYang, a novel portable Artificial Intelligence Electrocardiogram (AI-ECG) device, can detect many kinds of abnormal heart disease and perform a single-lead ECG, but its reliability and validity among pregnant women is unclear. The...
Humans Artificial Intelligence Pregnancy Adult Electrocardiography Arrhythmias, Cardiac Female Reproducibility of Results Young Adult Heart Rate
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Investigation of Inter-Patient, Intra-Patient, and Patient-Specific Based Training in Deep Learning for Classification of Heartbeat Arrhythmia.

Cardiovascular engineering and technology Feb 26, 2025
Effective diagnosis of electrocardiogram (ECG) is one of the simplest and fastest ways to assess the heart's function. In the recent decade, various attempts have been made to automate the classification of electrocardiogram signals to detect heartbe...
Heart Rate Deep Learning Electrocardiography Action Potentials Predictive Value of Tests Databases, Factual Humans Signal Processing, Computer-Assisted Reproducibility of Results Arrhythmias, Cardiac Diagnosis, Computer-Assisted
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Deep Learning Approach for Automatic Heartbeat Classification.

Sensors (Basel, Switzerland) Feb 25, 2025
Arrhythmia is an irregularity in the rhythm of the heartbeat, and it is the primary method for detecting cardiac abnormalities. The electrocardiogram (ECG) identifies arrhythmias and is one of the methods used to diagnose cardiac issues. Traditional ...
Deep Learning Arrhythmias, Cardiac Humans Heart Rate Electrocardiography Algorithms Signal Processing, Computer-Assisted
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EffNet: an efficient one-dimensional convolutional neural networks for efficient classification of long-term ECG fragments.

Biomedical physics & engineering express Feb 21, 2025
Early Diagnosis of Cardiovascular disease (CVD) is essential to prevent a person from death in case of a cardiac arrhythmia. Automated ECG classification is required because manual classification by cardiologists is laborious, time-consuming, and pro...
Signal Processing, Computer-Assisted Arrhythmias, Cardiac Convolutional Neural Networks Electrocardiography Algorithms Humans Databases, Factual Neural Networks, Computer Cardiovascular Diseases
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Ventricular Arrhythmia Classification Using Similarity Maps and Hierarchical Multi-Stream Deep Learning.

IEEE transactions on bio-medical engineering Feb 20, 2025
OBJECTIVE: Ventricular arrhythmias are the primary arrhythmias that cause sudden cardiac death. We address the problem of classification between ventricular tachycardia (VT), ventricular fibrillation (VF) and non-ventricular rhythms (NVR).
Tachycardia, Ventricular Ventricular Fibrillation Algorithms Deep Learning Electrocardiography Signal Processing, Computer-Assisted Arrhythmias, Cardiac Humans
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Antifreezing Ultrathin Bioionic Gel-Based Wearable System for Artificial Intelligence-Assisted Arrhythmia Diagnosis in Hypothermia.

ACS nano Feb 17, 2025
Cardiovascular disease (CAD) is a major global public health issue, with mortality rates being significantly impacted by cold temperatures. Stable and reliable electrocardiogram (ECG) monitoring in cold environments is crucial for early detection and...
Electrocardiography Polymers Arrhythmias, Cardiac Gels Hypothermia Humans Artificial Intelligence Wearable Electronic Devices
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Thermo-responsive and phase-separated hydrogels for cardiac arrhythmia diagnosis with deep learning algorithms.

Biosensors & bioelectronics Feb 14, 2025
Adhesive epidermal hydrogel electrodes are essential for achieving robust signal transduction and cardiac arrhythmia diagnosis, but detachment of conventional adhesive dressings easily causes secondary damage to delicate wound tissues due to lack of ...
Algorithms Temperature Deep Learning Humans Electrodes Arrhythmias, Cardiac Hydrogels Wearable Electronic Devices Biosensing Techniques Electrocardiography
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An arrhythmia classification using a deep learning and optimisation-based methodology.

Journal of medical engineering & technology Feb 14, 2025
The work proposes a methodology for five different classes of ECG signals. The methodology utilises moving average filter and discrete wavelet transformation for the remove of baseline wandering and powerline interference. The preprocessed signals ar...
Arrhythmias, Cardiac Deep Learning Humans Wavelet Analysis Electrocardiography Algorithms Signal Processing, Computer-Assisted
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Active learning and margin strategies for arrhythmia classification in implantable devices.

Computers in biology and medicine Feb 13, 2025
BACKGROUND AND OBJECTIVES: The massive storage of cardiac arrhythmic episodes from Implantable Cardioverter Defibrillators (ICD) and the advent of new artificial intelligence algorithms are opening up new opportunities for electrophysiological knowle...
Defibrillators, Implantable Algorithms Humans Supervised Machine Learning Machine Learning Arrhythmias, Cardiac
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Deep CNN-based detection of cardiac rhythm disorders using PPG signals from wearable devices.

PloS one Feb 12, 2025
Cardiac rhythm disorders can manifest in various ways, such as the heart rate being too fast (tachycardia) or too slow (bradycardia), irregular heartbeats (like atrial fibrillation-AF, ventricular fibrillation-VF), or the initiation of heartbeats in ...
Signal Processing, Computer-Assisted Humans Heart Rate Arrhythmias, Cardiac Photoplethysmography Neural Networks, Computer Atrial Fibrillation Electrocardiography Wearable Electronic Devices
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