Background Coronary microvascular dysfunction (CMD) is associated with a poor prognosis but is difficult to diagnose non-invasively. In a recent paper, ST-segment depression on exercise-ECG was found ...
Heart rate variability (HRV) represents the physiological variation in the time interval between consecutive heartbeats, reflecting the complex interplay between the autonomic nervous system and ...
Director Jung Hyun-sook of the Seoul Health Screening Center at Gangbuk Samsung Hospital, who saved patients thanks to AI (artificial intelligence) applied to electrocardiogram (ECG) devices, said, ...
Recently, a research team from the Hefei Institutes of Physical Science of the Chinese Academy of Sciences, has developed a new deep learning method that improves the classification accuracy of mixed ...
Background: Brain natriuretic peptide (BNP) is a key heart failure biomarker. Single-lead electrocardiograms (ECGs) from wearable devices offer valuable diagnostic and prognostic insights. We ...
Abstract: Automated electrocardiogram (ECG) classification tasks play a crucial role in clinical but face challenges due to the scarcity of accessible and well-labeled data. ECG data augmentation is ...
Heart disease remains the leading cause of death worldwide, and although electrocardiography (ECG) is critical for diagnosis, interpreting ECG signals requires extensive training. Current machine ...
Abnormal ventricular depolarization, evident as a broad QRS complex on an ECG, is traditionally categorized into left bundle‐branch block (LBBB) and right bundle‐branch block or nonspecific ...
ABSTRACT: Fourier transform provides frequency spectrum of signal for feature extraction, wavelet classifier, matching filter design, and etc. Visualization the spectrum of an indexed ...
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