Digital Signal Processing of ECG Signals for the Diagnosis of Heart Diseases

The proposed system for the Digital Signal Processing of ECG signals offers a highly reliable and automated solution for the diagnosis of heart diseases. By effectively implementing digital filters and feature extraction algorithms on an embedded platform, the system successfully cleans raw ECG data and identifies critical cardiac abnormalities in real-time. The integration of IoT capabilities allows for continuous remote patient monitoring, significantly reducing the burden on healthcare facilities and minimizing the risk of delayed treatment. While severe motion artifacts from patient movement remain a challenge requiring advanced adaptive filtering, the system demonstrates immense potential for modern telehealth. Future enhancements could include the deployment of deep learning models (such as CNNs) directly onto edge devices for even higher classification accuracy across a broader spectrum of cardiovascular diseases.

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