Key result
MATLAB signal processing using high-pass filtering and squaring successfully calculated a heart rate of 46.15 bpm from the ECG dataset, enabling the detection of bradycardia.
Digital signal filtering of ECG data using MATLAB provides a fast computational method for detecting bradycardia.
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Supports MATLAB ECG processing for bradycardia detection; leaves open clinical validation.
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. MATLAB ECG signal processing was evaluated on Heart rate calculation and bradycardia detection. MATLAB signal processing using high-pass filtering and squaring successfully calculated a heart rate of 46.15 bpm from the ECG dataset, enabling the detection of bradycardia.
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