Cardiac signal processing

A MATLAB-based interface for analyzing and interpreting cardiac signals.

Project Overview

This was one of my first serious software development projects using MATLAB, focused on biomedical signal processing. The goal was to create a user-friendly interface that allows users to upload cardiac signal data and extract meaningful metrics and visualizations.

Key Features

• User-uploaded signal support: The interface allows users to load their own ECG or cardiac signal files for processing.
• Signal visualization: Plots time-series data with adjustable zoom and scaling.
• Feature extraction: The app identifies peaks, intervals, and can provide HR (heart rate) calculations.
• Modular design: Structured with functions to allow easy extensión or modification.

Technologies Used

• MATLAB App Designer: Used to create the graphical user interface.
• Signal Processing Toolbox: For filtering, peak detection, and feature analysis.
• Basic GUI controls: Sliders, dropdowns, and plots for interaction and parameter tuning.

What Did I Learn?

• The basics of MATLAB programming and how to build graphical interfaces using App Designer.
• Signal processing principles such as filtering, noise reduction, and peak detection.
• A foundational understanding of cardiac physiology and how it reflects in signal patterns (e.g., QRS complexes).
• Designing modular code that separates logic, user interaction, and visualization.

Final Thoughts

Although this project was extremely challenging at the time -- given that I was learning MATLAB, signal processing, and medical terminology all at once -- it was a major milestone in my academic and technical development. It sparked my interest in biomedical engineering and laid the foundation for future work in health-related software.