ECG Signal Processing: Balancing Accuracy and Efficiency in Early Cardiovascular Disease Detection

An ECG signal processing approach that balances accuracy and efficiency in early cardiovascular disease detection.

An ECG signal processing approach that balances accuracy and efficiency in early cardiovascular disease detection. It is offered as a reference project: a complete, worked example of how a system like this is designed, built and evaluated, so that a developer can study it, run it and learn from it.

It suits learners who want to work with signals and wireless data: acquiring or simulating signals, filtering and extracting features, and evaluating the results.

The main parts are signal acquisition or simulation, filtering and feature extraction, a processing or learning model, and plots and a clear evaluation. The reference build uses Python, NumPy, SciPy, and MATLAB, with a clear project structure, setup instructions and sample data so that it can be run and extended.