Higher Order Filter and FrFT Based ECG Signal Analysis

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This research paper presents a comprehensive methodology for Electrocardiogram (ECG) signal analysis utilizing advanced techniques including higher-order filtering, Fractional Fourier Transform (FrFT), and Particle Swarm Optimization (PSO). ECG signals, critical for diagnosing and monitoring cardiac health, often suffer from noise and artifacts that obscure vital diagnostic features. To address this, an 8th-order Butterworth Infinite Impulse Response (IIR) filter is used, which effectively eliminates noise while preserving essential signal characteristics such as P, QRS, and T waves. The FrFT is introduced to provide a flexible time-frequency representation, facilitating a more detailed analysis of non-stationary ECG signals. This transform allows for enhanced detection of transient cardiac events and improves the accuracy of feature extraction by adapting to the specific characteristics of the ECG signal. Furthermore, PSO is applied to optimize the feature selection process.

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