ECG And Sound Based Angiography System

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Dhakshanadevi S; Dharika K; Geevithra G; Dr.S.Balakrishnan

ECG And Sound Based Angiography System

Authors: Dhakshanadevi S, Dharika K, Geevithra G, Dr.S.Balakrishnan

Unique Paper ID: 176874
Volume: 11
Issue: 11
PageNo: 8008-8013

Keywords: Electrocardiogram (ECG) Angiography Arterial sound data Signal processing Machine Learning algorithms Support Vector Machine (SVM) Extreme Gradient Boosting (XGBoost) Feature Extraction Non-invasive Diagnostics Cardiovascular Health.

Abstract:
Objective: The objective of this study is to develop a non-invasive diagnostic tool that integrates ECG signals with arterial sound data for the detection and analysis of blockages. Methods: The proposed system utilizes ECG and arterial sound signals, processed using complex signal processing techniques. Feature extraction methodologies are employed to drive meaningful data, which is then analyzed using machine learning algorithms to detect blockages. Results: The Detected blockages will be viewed in Dashboard in the form of signals or waveforms. Comparative studies with standard angiographic methods show promising results, validating the system’s effectiveness in a non-invasive manner. Discussion: This innovative method will minimize patient risk with traditional invasive angiographic procedures. The integration of ECG and arterial sound data enhances diagnostic capabilities, offering a cost-effective and reliable alternative for cardiovascular diagnostics.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 8008-8013

ECG And Sound Based Angiography System

Available:https://ijirt.org/article?manuscript=176874

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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