Evaluation of electrocardiogram signals classification using CNN, SVM, and LSTM algorithm: A review
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 …
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
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 …
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 …
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 …
Early diagnosis was essential in providing intervention for patients suffering from cardiac …
Machine algorithm for heartbeat monitoring and arrhythmia detection based on ECG systems
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 …
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
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 …
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
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 …
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
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 …
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 …
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
This paper introduces and evaluates a general construct for trading off accuracy and overall
execution duration in classification-based machine perception problems—namely, the …
execution duration in classification-based machine perception problems—namely, the …