ECG R-Peak Detection Using MATLAB

This repository contains a MATLAB script designed to detect R-peaks in ECG (Electrocardiogram) signals using advanced signal processing techniques. The approach involves preprocessing, feature extraction, and logic for accurate R-peak detection in raw ECG data.

Features

1. Preprocessing

• Bandpass Filtering: Removes baseline wander and high-frequency noise while preserving essential features.
• Normalization and Differentiation: Enhances the QRS complex for better peak detection.

2. Feature Extraction

• Shannon Energy Envelope: Highlights significant energy changes in the ECG signal.
• Moving Average Filters: Smoothens the signal for peak enhancement.

3. R-Peak Detection Logic

• Combines squaring, filtering, and a refined search method.
• Identifies peaks in a neighborhood of candidate points for accurate localization.

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Workflow

The detection process is divided into four major steps:

1. Signal Extraction and Preprocessing

• Load the ECG signal from a .mat file.
• Apply a Chebyshev Type I Bandpass Filter to eliminate noise.
• Perform differentiation and normalization to emphasize QRS complexes.

2. Shannon Energy Envelope Extraction

• Compute the Shannon Energy Envelope to amplify regions with high energy.
• Smooth the signal using a moving average filter.

3. Peak Estimation

• Differentiate and square the smoothed signal to highlight peaks.
• Use an additional moving average filter to refine candidate peaks.

4. R-Peak Refinement

• Detect peaks from the smoothed signal.
• Refine R-peak positions by searching within a ±25-sample window.
• Overlay detected R-peaks on the original ECG signal.