Computerized heart sounds analysis

Area of Science:

• Biomedical Signal Processing
• Cardiovascular Diagnostics
• Time-Frequency Analysis

Background:

• Phonocardiogram (PCG) signals contain crucial diagnostic information.
• Accurate analysis of PCG signals requires advanced signal processing techniques.
• Existing methods may not fully capture the complex time-frequency characteristics of PCG.

Purpose of the Study:

• To synthesize and compare the efficacy of various time-frequency transforms for PCG signal analysis.
• To evaluate the utility of Fast Fourier Transform (FFT), Short-Time Fourier Transform (STFT), Wigner Distribution (WD), and Wavelet Transform (WT) for PCG.
• To determine how these methods aid in obtaining qualitative and quantitative measurements of PCG time-frequency characteristics.

Main Methods:

• Comparative analysis of FFT, STFT, WD, and WT applied to PCG signals.
• Evaluation of the capability of each transform to extract relevant signal features.
• Assessment of the complementary nature of different transforms in time-frequency analysis.

Main Results:

• FFT effectively determines the frequency content of PCG signals.
• STFT, WD, and WT provide detailed time-frequency (TF) features of PCG signals.
• These transforms collectively offer comprehensive insights for clinical measurements and diagnosis.

Conclusions:

• The studied transforms (FT, STFT, WD, CWT, DWT, PWT) are complementary for TF analysis of PCG signals.
• These methods enhance the ability to obtain qualitative and quantitative measurements of PCG characteristics.
• The comprehensive analysis aids clinicians in diagnosing cardiovascular conditions through PCG interpretation.