ECG-iCOVIDNet: Interpretable AI model to identify changes in the ECG signals of post-COVID subjects

A Agrawal, A Chauhan, MK Shetty, MD Gupta… - Computers in Biology …, 2022 - Elsevier
Objective Studies showed that many COVID-19 survivors develop sub-clinical to clinical
heart damage, even if subjects did not have underlying heart disease before COVID. Since …

[HTML][HTML] Deep learning for ECG classification: A comparative study of 1D and 2D representations and multimodal fusion approaches

H Narotamo, M Dias, R Santos, AV Carreiro… - … Signal Processing and …, 2024 - Elsevier
The improved diagnosis of cardiovascular diseases (CVD) from electrocardiograms (ECG)
may help prevent their severity. Since Deep Learning (DL) became popular, several DL …

[HTML][HTML] A novel concatenate feature fusion RCNN architecture for sEMG-based hand gesture recognition

P Xu, F Li, H Wang - PloS one, 2022 - journals.plos.org
Hand gesture recognition tasks based on surface electromyography (sEMG) are vital in
human-computer interaction, speech detection, robot control, and rehabilitation applications …

[HTML][HTML] SAR model for accurate detection of multi-label arrhythmias from electrocardiograms

L Yang, Y Zheng, Z Liu, R Tang, L Ma, Y Chen… - Heliyon, 2023 - cell.com
Objective Arrhythmias are prevalent symptoms of cardiovascular disease, necessitating
accurate and timely detection to mitigate associated risks. Detecting arrhythmias from ECGs …

Islanding Detection Using Transformer Neural Networks

E David, JR Orillaza, JR Pedrasa - 2024 IEEE 4th International …, 2024 - ieeexplore.ieee.org
Unintentional islanding is becoming a significant concern for distribution utilities due to the
growing use of solar photovoltaic systems. These unintentional islands pose a threat to the …

Wireless Electrocardiography and Impedance Cardiography Devices Using a Network Time Protocol for Synchronized Data

S Orsolini, E Pannicke, I Fomin… - 2021 43rd Annual …, 2021 - ieeexplore.ieee.org
During minimally invasive and image-guided procedures, vital parameters have to be
recorded for patient safety. In the Magnetic Resonance Tomograph (MRT) environment the …

[PDF][PDF] Cardiac arrhythmias classification in a low-power processor with TensorFlow Lite

L Landi, I Chatzigiannakis - ichatz.me
The World Health Organization estimated that 17.9 million people die each year from
cardiovascular diseases (CVDs), an estimated 32% of all deaths worldwide. 85% of all CVD …

Convolution-based models for automated interpretation of the electrocardiogram

P Pantelidis - 2021 - search.proquest.com
Methods: We retrieved ECG samples from an online databank, called PTB-XL. After pre-
processing them, we applied InceptionTime, MINIROCKET and a “custom” model we …