Key result
A fuzzy-based multi-objective algorithm using Fast Fourier Transform achieved an efficiency of approximately 98.7% in detecting cardiovascular abnormalities from ECG signals.
Why the study?
Does a fuzzy-based multi-objective genetic algorithm using FFT accurately detect cardiovascular abnormalities from ECG signals?
Population
ECG signals from a database (e.g., MIT-BIH arrhythmia database) for detection of cardiovascular abnormalities
Design
Other
Authors
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Should not yet change clinical ECG workflows; leaves open prospective validation in real-world cohorts.
Does a fuzzy-based multi-objective genetic algorithm using FFT accurately detect cardiovascular abnormalities from ECG signals?
A novel FFT-based multi-objective genetic algorithm demonstrated high efficiency (98.7%) in detecting cardiovascular abnormalities from ECG signals.
Prasad et al. (2017) studied Cardiovascular abnormalities. Fuzzy-based multi-objective algorithm using Fast Fourier Transform (FFT) was evaluated on Detection efficiency of abnormalities. A fuzzy-based multi-objective algorithm using Fast Fourier Transform achieved an efficiency of approximately 98.7% in detecting cardiovascular abnormalities from ECG signals.
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