Evaluation of electrocardiogram signals classification using CNN, SVM, and LSTM algorithm: A review

OMA Ali, SW Kareem… - 2022 8th International …, 2022 - ieeexplore.ieee.org
The non-stationary signals of Electrocardiogram (ECG) are widely utilized to assess
heartbeat rate and tune the major goal of this study is to give an overview of ECG …

[HTML][HTML] Identification and authentication in healthcare internet-of-things using integrated fog computing based blockchain model

S Shukla, S Thakur, S Hussain, JG Breslin, SM Jameel - Internet of Things, 2021 - Elsevier
Abstract The healthcare Internet-of-Things (IoT) offers many benefits including data
transmission in real-time mode, the ability to monitor the physiological state of the patient in …

An intelligent learning approach for improving ECG signal classification and arrhythmia analysis

AK Sangaiah, M Arumugam, GB Bian - Artificial intelligence in medicine, 2020 - Elsevier
The recognition of cardiac arrhythmia in minimal time is important to prevent sudden and
untimely deaths. The proposed work includes a complete framework for analyzing the …

Automated arrhythmia classification using depthwise separable convolutional neural network with focal loss

Y Lu, M Jiang, L Wei, J Zhang, Z Wang, B Wei… - … Signal Processing and …, 2021 - Elsevier
Arrhythmia was one of the primary causes of morbidity and mortality among cardiac patients.
Early diagnosis was essential in providing intervention for patients suffering from cardiac …

Machine algorithm for heartbeat monitoring and arrhythmia detection based on ECG systems

AI Taloba, R Alanazi, OR Shahin… - Computational …, 2021 - Wiley Online Library
Cardiac arrhythmia is an illness in which a heartbeat is erratic, either too slow or too rapid. It
happens as a result of faulty electrical impulses that coordinate the heartbeats. Sudden …

Migrating intelligence from cloud to ultra-edge smart IoT sensor based on deep learning: An arrhythmia monitoring use-case

S Sakib, MM Fouda, ZM Fadlullah… - … and Mobile Computing …, 2020 - ieeexplore.ieee.org
Traditionally, the Internet of Things (IoT) devices, deployed on the ultra-edge of the network,
lack computation, and energy resources. In this paper, we press on the need to go beyond …

Asynchronous federated learning-based ECG analysis for arrhythmia detection

S Sakib, MM Fouda, ZM Fadlullah… - 2021 IEEE …, 2021 - ieeexplore.ieee.org
With the rapid elevation of technologies such as the Internet of Things (IoT) and Artificial
Intelligence (AI), the traditional cloud analytics-based approach is not suitable for a long time …

A practical system based on CNN-BLSTM network for accurate classification of ECG heartbeats of MIT-BIH imbalanced dataset

A Shoughi, MB Dowlatshahi - 2021 26th international computer …, 2021 - ieeexplore.ieee.org
ECG beats have a key role in the reduction of fatality rate arising from cardiovascular
diseases (CVDs) by using Arrhythmia diagnosis computer-aided systems and get the …

Arrhythmia diagnosis of young martial arts athletes based on deep learning for smart medical care

J Zhuang, J Sun, G Yuan - Neural Computing and Applications, 2023 - Springer
Cardiovascular and cerebrovascular diseases are a serious threat to human health and
increase the annual death ratio at a considerable pace. This is not uncommon even among …

Scheduling IDK classifiers with arbitrary dependences to minimize the expected time to successful classification

T Abdelzaher, K Agrawal, S Baruah, A Burns… - Real-Time …, 2023 - Springer
This paper introduces and evaluates a general construct for trading off accuracy and overall
execution duration in classification-based machine perception problems—namely, the …