[HTML][HTML] Comprehensive survey of computational ECG analysis: Databases, methods and applications
Electrocardiogram (ECG) recordings are indicative for the state of the human heart.
Automatic analysis of these recordings can be performed using various computational …
Automatic analysis of these recordings can be performed using various computational …
[HTML][HTML] Analysis of various techniques for ECG signal in healthcare, past, present, and future
Cardiovascular diseases are the primary reason for mortality worldwide. As per WHO survey
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
report in 2019, 17.9 million people died due to CVDs, accounting for 32% of all global …
Wavesplit: End-to-end speech separation by speaker clustering
We introduce Wavesplit, an end-to-end source separation system. From a single mixture, the
model infers a representation for each source and then estimates each source signal given …
model infers a representation for each source and then estimates each source signal given …
Deep learning in cardiology
P Bizopoulos, D Koutsouris - IEEE reviews in biomedical …, 2018 - ieeexplore.ieee.org
The medical field is creating large amount of data that physicians are unable to decipher
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
Fetal electrocardiograms, direct and abdominal with reference heartbeat annotations
Monitoring fetal heart rate (FHR) variability plays a fundamental role in fetal state
assessment. Reliable FHR signal can be obtained from an invasive direct fetal …
assessment. Reliable FHR signal can be obtained from an invasive direct fetal …
[HTML][HTML] State-of-the-art deep learning methods on electrocardiogram data: systematic review
Background Electrocardiogram (ECG) is one of the most common noninvasive diagnostic
tools that can provide useful information regarding a patient's health status. Deep learning …
tools that can provide useful information regarding a patient's health status. Deep learning …
A review of signal processing techniques for non-invasive fetal electrocardiography
Fetal electrocardiography (fECG) is a promising alternative to cardiotocography continuous
fetal monitoring. Robust extraction of the fetal signal from the abdominal mixture of maternal …
fetal monitoring. Robust extraction of the fetal signal from the abdominal mixture of maternal …
Non-invasive fetal ECG analysis
Despite the important advances achieved in the field of adult electrocardiography signal
processing, the analysis of the non-invasive fetal electrocardiogram (NI-FECG) remains a …
processing, the analysis of the non-invasive fetal electrocardiogram (NI-FECG) remains a …
Fetal ECG extraction from maternal ECG using attention-based CycleGAN
A non-invasive fetal electrocardiogram (FECG) is used to monitor the electrical pulse of the
fetal heart. Decomposing the FECG signal from the maternal ECG (MECG) is a blind source …
fetal heart. Decomposing the FECG signal from the maternal ECG (MECG) is a blind source …
[HTML][HTML] Map** of crowdsourcing in health: systematic review
P Créquit, G Mansouri, M Benchoufi, A Vivot… - Journal of medical …, 2018 - jmir.org
Background Crowdsourcing involves obtaining ideas, needed services, or content by
soliciting Web-based contributions from a crowd. The 4 types of crowdsourced tasks …
soliciting Web-based contributions from a crowd. The 4 types of crowdsourced tasks …