This project performs ECG (Electrocardiogram) signal analysis using MATLAB for the course Signals and Systems (BEC403).
The ECG signal is processed using signal processing techniques to extract important features such as R-peaks, RR intervals, heart rate, and heart rate variability (HRV).
The ECG data used in this project is taken from the MIT-BIH Arrhythmia Database, a widely used biomedical dataset for cardiovascular signal analysis.
Electrocardiogram (ECG) signals represent the electrical activity of the human heart over time. Analyzing ECG signals helps in detecting abnormal heart conditions such as arrhythmia, bradycardia, and tachycardia.
In this project, MATLAB is used to perform ECG signal processing and analysis. The program loads ECG data from the dataset, filters noise from the signal, detects R-peaks, calculates RR intervals, and determines heart rate and heart rate variability.
The final results are displayed through graphical plots that visualize the ECG waveform and its extracted features.
Dataset used: MIT-BIH Arrhythmia Database
Source:
https://physionet.org/content/mitdb/
Dataset characteristics:
- Sampling frequency: 360 Hz
- ECG signals stored in .dat format
- Two-channel ECG recordings
In this project, only the first channel of the ECG signal is used for analysis.
The first 10 seconds of ECG data are extracted for processing.
The ECG signal analysis is performed using the following steps:
- Load ECG data from the MIT-BIH dataset
- Extract the first 10 seconds of ECG signal
- Apply bandpass filtering (0.5 Hz – 40 Hz)
- Detect R-peaks using MATLAB
findpeaks()function - Calculate RR intervals
- Compute heart rate (BPM)
- Calculate heart rate variability (HRV)
- Generate visualization plots for ECG analysis
Main MATLAB script used in this project:
ecg_full_analysis.m
Key MATLAB functions used:
| Function | Purpose |
|---|---|
| fread() | Read ECG data file |
| butter() | Design Butterworth bandpass filter |
| filtfilt() | Apply zero-phase filtering |
| findpeaks() | Detect R-peaks in ECG signal |
| diff() | Calculate RR intervals |
| mean() | Calculate average heart rate |
| std() | Calculate heart rate variability |
The MATLAB program generates multiple plots to visualize the ECG signal and its features.
From the ECG analysis:
Average Heart Rate: 74.86 BPM
Heart Rate Variability: 0.218 sec
Mean RR Interval: 0.848 sec
Diagnosis: Normal ECG
- Install MATLAB.
- Download the MIT-BIH Arrhythmia Dataset from PhysioNet.
- Update the dataset path in the MATLAB script:
filename = 'data/mit-bih-arrhythmia-database-1.0.0/234.dat';
- Run the MATLAB script:
ecg_full_analysis.m
- MATLAB will generate ECG plots and display the analysis results.
ECG signal analysis is widely used in:
- Heart disease detection
- Arrhythmia monitoring
- Biomedical signal processing
- Wearable health devices
- Remote patient monitoring systems
Mahendra M
Electronics and Communication Engineering
The National Institute of Engineering
Mysuru, India
This project is created for academic and educational purposes.