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Diagnose von Herzkrankheiten anhand des Elektrokardiogramms

Diagnose von Herzkrankheiten anhand des Elektrokardiogramms

Shadi Obaid / Umar Alqasemi

55,87 €
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Editorial:
KS OmniScriptum Publishing
Año de edición:
2024
Materia
Informática: cuestiones generales
ISBN:
9786207595990
55,87 €
IVA incluido
Disponible

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Sobre IBD

Die Klassifizierung von EKG-Signalen auf manuelle oder traditionelle Weise ist ein Bereich, der durch ein automatisches Klassifizierungssystem für EKG-Signale verbessert werden könnte. In dieser Arbeit wird ein verbessertes Software-System für die computergestützte Diagnose (CAD) zur automatischen Klassifizierung von EKG-Signalen eingeführt. Insgesamt 480 EKG-Signale wurden als Datensatz für diese Studie aus der MIT-BIH Arrhythmie-Datenbank entnommen; diese Datensätze enthalten 96 normale EKG-Signale sowie 384 abnormale EKG-Signale, die zu vier Arten von Herzanomalien gehören, nämlich ventrikuläres Couplet, ventrikuläre Tachykardie, ventrikuläre Bigeminie und ventrikuläres Flimmern, wobei jede dieser Arten ebenfalls 96 EKG-Signale enthält. Dann wurde eine erneute Abtastung für alle gegebenen Signale mit 360 Abtastungen pro Sekunde durchgeführt, mit Ausnahme der VF-Signale, die mit 250 Abtastungen pro Sekunde neu abgetastet wurden. Danach wurde eine iterative Merkmalsextraktion mit Hilfe der Classification Learner App in MATLAB durchgeführt.

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