Automatic measure of the split in the second cardiac sound by using the wavelet transform technique

Area of Science:

• Biomedical Engineering
• Cardiology
• Signal Processing

Background:

• The second heart sound (S2) comprises aortic (A2) and pulmonary (P2) valve closures.
• A delay between A2 and P2, known as S2 splitting, can indicate cardiac pathologies.
• Accurate measurement of S2 splitting is crucial for diagnosing various cardiovascular conditions.

Purpose of the Study:

• To develop and validate an automatic technique for measuring S2 splitting in phonocardiogram (PCG) signals.
• To quantify the time delay between the A2 and P2 components of S2.
• To assess the utility of wavelet transforms in analyzing S2 splitting for medical diagnosis.

Main Methods:

• Utilized discrete wavelet transform (DWT) and continuous wavelet transform (CWT) for PCG signal analysis.
• Developed an algorithm to automatically identify the A2 and P2 components within the S2 signal.
• Estimated the time delay between the identified A2 and P2 components to quantify S2 splitting.

Main Results:

• The wavelet transform-based method effectively identified the A2 and P2 components of S2.
• The technique accurately measured the splitting (time delay) between A2 and P2 in both normal and pathological PCG signals.
• Wavelet analysis provided significant information and features related to S2 splitting and its components.

Conclusions:

• Wavelet transforms are powerful tools for analyzing the complex features of S2 splitting.
• The developed automatic technique offers a reliable method for quantifying S2 splitting.
• This approach has the potential to significantly aid in the medical diagnosis of cardiac conditions through PCG analysis.