Key result
Fast Fourier transform analysis reliably isolates dominant ECG frequencies to support automated heart rate diagnosis.
Why the study?
This study aimed to analyze electrocardiogram (ECG) signals using the fast Fourier transform (FFT) method to support heart rate diagnosis.
Does fast Fourier transform (FFT) analysis of digitized ECG signals accurately determine dominant frequency for heart rate diagnosis compared to normal ECG signals?
Does fast Fourier transform (FFT) analysis of digitized ECG signals accurately determine dominant frequency for heart rate diagnosis compared to normal ECG signals?
Answers are grounded in this paper and cite their sources.
Fast Fourier transform (FFT) analysis of digitized ECG waveforms can identify dominant signal frequencies (1.0332 Hz to 1.6172 Hz) to support automated heart rate diagnostics.
This study aims to analyze electrocardiogram (ECG) signals using the fast Fourier transform (FFT) method to support heart rate diagnosis. The data used consists of nine recordings of patient ECG signals obtained in graphic form, then converted into numerical data using PlotDigitizer software. Furthermore, the data was analyzed in the frequency domain using the FFT algorithm formulated through MATLAB software. The transformation results showed that the dominant frequency of each ECG signal ranged from 1.0332 Hz to 1.6172 Hz. A comparison between the FFT results and normal ECG signals was conducted to evaluate the suitability of the waveform and rhythm. Quantitative evaluation was conducted using the mean squared error (MSE) method to measure the level of difference between signals. The results confirm that the frequency-based method significantly contributes to more accurate measurements and greater efficiency in heart rate diagnostics. This method also supports the advancement of sophisticated techniques in biomedical signal processing.
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Putri et al. (2026) studied Heart rate diagnosis via ECG signal analysis (n=9). Fast Fourier transform (FFT) method via MATLAB vs. Normal ECG signals was evaluated on Dominant frequency of ECG signals and signal difference measured by mean squared error (MSE). Fast Fourier transform analysis of 9 ECG recordings identified dominant frequencies ranging from 1.0332 Hz to 1.6172 Hz for heart rate diagnosis.
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