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[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 …
Deep learning on 1-D biosignals: a taxonomy-based survey
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 …
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
Sažetak Deep emotional traumas in societies overwhelmed by large-scale human disasters,
like, global pandemic diseases, natural disasters, man-made tragedies, war conflicts, social …
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
Physiological signals are widely used to perform medical assessment for monitoring an
extensive range of pathologies, usually related to cardio-vascular diseases. Among these …
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
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 …
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
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 …
cardiac disorders. The QRS waves on the ECG signal are essential in diagnosing these …
Spiking neural networks: background, recent development and the NeuCube architecture
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 …
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
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 …
solve the imbalance problem in electrocardiogram (ECG) heartbeats classification. Four …
Lightweight shufflenet based cnn for arrhythmia classification
Recent advances in artificial intelligence (AI) and continuous monitoring of patients using
wearable devices have enhanced the accuracy of diagnosing various arrhythmias, from the …
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
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 …
QRS complex and T-wave, plays a crucial role in the treatment of cardiovascular disease …