[HTML][HTML] Analysis of various techniques for ECG signal in healthcare, past, present, and future

T Anbalagan, MK Nath, D Vijayalakshmi… - Biomedical Engineering …, 2023‏ - Elsevier
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 …

Deep learning on 1-D biosignals: a taxonomy-based survey

N Ganapathy, R Swaminathan… - Yearbook of medical …, 2018‏ - thieme-connect.com
Objectives: Deep learning models such as convolutional neural networks (CNNs) have been
applied successfully to medical imaging, but biomedical signal analysis has yet to fully …

Impact of human disasters and COVID-19 pandemic on mental health: potential of digital psychiatry

K Ćosić, S Popović, M Šarlija, I Kesedžić - Psychiatria Danubina, 2020‏ - hrcak.srce.hr
Sažetak Deep emotional traumas in societies overwhelmed by large-scale human disasters,
like, global pandemic diseases, natural disasters, man-made tragedies, war conflicts, social …

An advanced bio-inspired photoplethysmography (PPG) and ECG pattern recognition system for medical assessment

F Rundo, S Conoci, A Ortis, S Battiato - Sensors, 2018‏ - mdpi.com
Physiological signals are widely used to perform medical assessment for monitoring an
extensive range of pathologies, usually related to cardio-vascular diseases. Among these …

[HTML][HTML] Study of the few-shot learning for ECG classification based on the PTB-XL dataset

K Pałczyński, S Śmigiel, D Ledziński, S Bujnowski - Sensors, 2022‏ - mdpi.com
The electrocardiogram (ECG) is considered a fundamental of cardiology. The ECG consists
of P, QRS, and T waves. Information provided from the signal based on the intervals and …

A real-time embedded system to detect QRS-complex and arrhythmia classification using LSTM through hybridized features

M Karri, CSR Annavarapu - Expert Systems with Applications, 2023‏ - Elsevier
The electrocardiogram (ECG) is an extremely valuable medical examination for monitoring
cardiac disorders. The QRS waves on the ECG signal are essential in diagnosing these …

Spiking neural networks: background, recent development and the NeuCube architecture

C Tan, M Šarlija, N Kasabov - Neural Processing Letters, 2020‏ - Springer
This paper reviews recent developments in the still-off-the-mainstream information and data
processing area of spiking neural networks (SNN)—the third generation of artificial neural …

[HTML][HTML] A novel multi-module neural network system for imbalanced heartbeats classification

J Jiang, H Zhang, D Pi, C Dai - Expert Systems with Applications: X, 2019‏ - Elsevier
In this paper, a novel multi-module neural network system named MMNNS is proposed to
solve the imbalance problem in electrocardiogram (ECG) heartbeats classification. Four …

Lightweight shufflenet based cnn for arrhythmia classification

H Tesfai, H Saleh, M Al-Qutayri, MB Mohammad… - IEEE …, 2022‏ - ieeexplore.ieee.org
Recent advances in artificial intelligence (AI) and continuous monitoring of patients using
wearable devices have enhanced the accuracy of diagnosing various arrhythmias, from the …

A comprehensive review of computer-based Techniques for R-peaks/QRS complex detection in ECG signal

H Dogan, RO Dogan - Archives of Computational Methods in Engineering, 2023‏ - Springer
Electrocardiogram (ECG) signal, which is composite of multiple segments such as P-wave,
QRS complex and T-wave, plays a crucial role in the treatment of cardiovascular disease …