HEART MURMUR
OUR PROJECT
This project focuses on the analysis and detection of heart murmurs and arrhythmias using heart sound signals. Audio data, captured via a stethoscope (e.g., 14998_MV.wav), undergo preprocessing with band-pass filtering (20–1500 Hz) to remove noise. The signal’s envelope is extracted using the Hilbert transform, followed by peak detection to identify S1 and S2 sounds, segmenting the heart cycle into systolic and diastolic intervals.
Heart rate is estimated from peak intervals, and murmurs are identified based on abnormal frequency patterns. Additionally, the system detects arrhythmias such as bradycardia, tachycardia, atrial fibrillation, and heart block. Time-frequency analysis using Short-Time Fourier Transform (STFT) further aids in visualizing sound characteristics.
This project demonstrates how heart audio recordings, combined with signal processing techniques, can offer early detection of cardiac abnormalities and support future automated diagnostics.
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