ECG Arrhythmia Measurement and Classification for Portable Monitoring

Globally, cardiovascular disease kills more than 500000 people every year, thus becoming the primary reason for death. Nevertheless, cardiovascular health monitoring is essential for accurate analysis and therapy of heart disease. In this work, a novel deep learning-based StrIppeD NAS-Network (SID-N...

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Veröffentlicht in:	Measurement science review Jg. 24; H. 4; S. 118 - 128
Hauptverfasser:	P Ajitha Gladis, K., Ahilan, A, Muthukumaran, N, Jenifer, L
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Bratislava Sciendo 01.08.2024 De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Schlagworte:	Abnormalities Accuracy Algorithms Arrhythmia arrhythmia classification Cardiac arrhythmia Classification Cluster analysis Clustering Deep learning Dingo optimization algorithm Discrete Wavelet Transform ECG signal Electrocardiography Fractal geometry Heart diseases Machine learning Parameter identification stripped convolution Telemedicine Vector quantization Waveforms Wavelet transforms
ISSN:	1335-8871, 1335-8871
Online-Zugang:	Volltext
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