AIMC Topic: Electrocardiography

Clear Filters Showing 41 to 50 of 1286 articles

False Crisis Alarms in Cardiopulmonary Monitoring:: Identification, Causes, and Clinical Implications.

Critical care nursing clinics of North America Mar 26, 2025
The systematic annotation of crisis alarms reveals a high number of false alarms for both ventricular tachycardia and asystole, which are best identified by inspecting simultaneous multilead electrocardiographs. Among the few true crisis alarms, 11 w...
Humans Tachycardia, Ventricular Heart Arrest Clinical Alarms Electrocardiography Monitoring, Physiologic Algorithms
View on PubMed DOI

Synthetic ECG signal generation using generative neural networks.

PloS one Mar 25, 2025
Electrocardiogram (ECG) datasets tend to be highly imbalanced due to the scarcity of abnormal cases. Additionally, the use of real patients' ECGs is highly regulated due to privacy issues. Therefore, there is always a need for more ECG data, especial...
Machine Learning Humans Algorithms Signal Processing, Computer-Assisted Neural Networks, Computer Heart Rate Electrocardiography
View on PubMed DOI

Weighted-VAE: A deep learning approach for multimodal data generation applied to experimental T. cruzi infection.

PloS one Mar 24, 2025
Chagas disease (CD), caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), represents a major public health concern in most of the American continent and causes 12,000 deaths every year. CD clinically manifests in two phases (acute and chron...
Electrocardiography Disease Models, Animal Trypanosoma cruzi Deep Learning Mice Humans Chagas Disease Animals Echocardiography
View on PubMed DOI

PULSE: A DL-Assisted Physics-Based Approach to the Inverse Problem of Electrocardiography.

IEEE transactions on bio-medical engineering Mar 21, 2025
This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) methods. Our objective is to enhance the accuracy and robustness of ECGI reconstructions. We reshape the ...
Humans Neural Networks, Computer Signal Processing, Computer-Assisted Deep Learning Image Processing, Computer-Assisted Heart Electrocardiography Algorithms Bayes Theorem
View on PubMed DOI

Automated detection of arrhythmias using a novel interpretable feature set extracted from 12-lead electrocardiogram.

Computers in biology and medicine Mar 15, 2025
The availability of large-scale electrocardiogram (ECG) databases and advancements in machine learning have facilitated the development of automated diagnostic systems for cardiac arrhythmias. Deep learning models, despite their potential for high ac...
Algorithms Databases, Factual Electrocardiography Signal Processing, Computer-Assisted Deep Learning Humans Arrhythmias, Cardiac
View on PubMed DOI

Multimodal machine learning for deception detection using behavioral and physiological data.

Scientific reports Mar 15, 2025
Deception detection is crucial in domains like national security, privacy, judiciary, and courtroom trials. Differentiating truth from lies is inherently challenging due to many complex, diversified behavioural, physiological and cognitive aspects. T...
Electrooculography Galvanic Skin Response Machine Learning India Female Lie Detection Electrocardiography Deception Humans Male Adult Electroencephalography
View on PubMed DOI

A deep Bi-CapsNet for analysing ECG signals to classify cardiac arrhythmia.

Computers in biology and medicine Mar 13, 2025
- In recent times, the electrocardiogram (ECG) has been considered as a significant and effective screening mode in clinical practice to assess cardiac arrhythmias. Precise feature extraction and classification are considered as essential concerns in...
Databases, Factual Deep Learning Signal Processing, Computer-Assisted Arrhythmias, Cardiac Electrocardiography Humans Neural Networks, Computer Algorithms
View on PubMed DOI

Reconstruction of ECG from ballistocardiogram using generative adversarial networks with attention.

Biomedical physics & engineering express Mar 12, 2025
Electrocardiogram (ECG) is widely used to provide early warning signals for cardiovascular diseases. However, traditional twelve-lead ECG monitoring methods and smartwatch-based home solutions are unable to achieve daily long-term monitoring. Therefo...
Humans Neural Networks, Computer Algorithms Heart Rate Ballistocardiography Generative Adversarial Networks Electrocardiography Signal Processing, Computer-Assisted
View on PubMed DOI

Deep learning-based prediction of atrial fibrillation from polar transformed time-frequency electrocardiogram.

PloS one Mar 10, 2025
Portable and wearable electrocardiogram (ECG) devices are increasingly utilized in healthcare for monitoring heart rhythms and detecting cardiac arrhythmias or other heart conditions. The integration of ECG signal visualization with AI-based abnormal...
Atrial Fibrillation Humans Neural Networks, Computer Fourier Analysis Electrocardiography Deep Learning Wearable Electronic Devices Signal Processing, Computer-Assisted
View on PubMed DOI

Integrated fusion approach for multi-class heart disease classification through ECG and PCG signals with deep hybrid neural networks.

Scientific reports Mar 8, 2025
Detection and classification of cardiovascular diseases are crucial for early diagnosis and prediction of heart-related conditions. Existing methods rely on either electrocardiogram or phonocardiogram signals, resulting in higher false positive rates...
Algorithms Electrocardiography Signal Processing, Computer-Assisted Humans Neural Networks, Computer Heart Diseases Phonocardiography
View on PubMed DOI
Popular Topics
Recent Journals