Key result
MATLAB-based ECG signal processing successfully detects bradycardia with a measured heart rate of ~46 bpm.
This biomedical engineering demonstration shows that basic high-pass filtering and signal squaring in MATLAB can isolate R-R peaks to compute heart rate and identify bradycardia from a single noisy PhysioNet ECG trace.
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MATLAB bradycardia detection on one ECG trace is hypothesis-generating; leaves open prospective validation before any clinical use.
Electrocardiogram is the record of electrical activity of heart. ECG is a test to detect and study normal rhythmic activity of the heart. Signal processing are very often used methods in a biomedical engineering research. This paper presents Bradycardia detection by utilization of digital signal filtering on electrocardiogram (ECG) using MATLAB. MATLAB was used to analyze and process ECG dataset gotten from Physionet online database with focus on R-R peaks to calculate the heartbeat, by applying high pass filtering and squaring the signal. The results obtained using MATLAB for ECG analysis and detection of arrhythmia is very fast and useful.
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Kabari et al. (2019) studied Bradycardia / cardiac arrhythmia (n=1). MATLAB digital signal processing (high-pass filtering and signal squaring) was evaluated on Heart rate calculation and bradycardia detection from R-R peak interval. MATLAB-based high-pass filtering and signal squaring detected bradycardia with a calculated heart rate of 46.15 bpm (R-R interval of 1.3 seconds) in a test ECG dataset.
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