Synthesis of neural network approaches used for ECG classification: Chapter Book,Used

Synthesis of neural network approaches used for ECG classification: Chapter Book,Used

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Cardiovascular diseases represent the most frequent cause of death in Europe. Consequently, their diagnoses appear a vital task. In cardiology unit, ECG signal still remains the dominant used tools for arrhythmia and heart diseases analysis. In fact, the ECG is a noninvasive tool to explore the functional heart sate. It is an electrical signal varying according to the electrical heart state. From the ECG signal, some significant parameters can be extracted. Generally, the durations and the shapes of the different waves are taken as bioindicators of certain cardiac anomalies. In fact, manual detection and classification of ECG waves is a difficult and annoying task especially for the analysis of the long recordings as in Holters and ambulatory cases. Besides, a detailed analysis of 12leads ECG used to identify the presence or the absence of the cardiac malfunction is also irritating. However, and due to large number of patients in intensive care units, the need for continuous heart activity monitoring is necessary requiring therefore the automatic analysis of the ECG signal.

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To facilitate a smooth return process, a Return Authorization (RA) Number is required for all returns. Returns without a valid RA number will be declined and may incur additional fees. You can request an RA number within 15 days of the original delivery date. For more details, please refer to our Return & Refund Policy page.

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Warranty

We provide a 2-year limited warranty, from the date of purchase for all our products.

If you believe you have received a defective product, or are experiencing any problems with your product, please contact us.

This warranty strictly does not cover damages that arose from negligence, misuse, wear and tear, or not in accordance with product instructions (dropping the product, etc.).

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