Innocent Still's Murmur in A Child

Innocent Flow Ejection Murmur

Normal Heart (S1 and S2)

S3 Heart Sound in a CHF Patient

Mitral Regurgitation (Multiple Clicks)

Mitral Valve Prolapse (MVP)

Ventricular Septal Defect (VSD)

Heart Energy Signature (HES) spectrogram (patent pending technology) allows to
represent heart sound mechanical energy and its components as an image,
simultaneously in time, frequency(pitch) with equally high resolution. In simple terms
this allows to:

a)       represent heart sound as a visual image
b)       obtain precise quantitative characteristics of heart sound power and
          pitch variation in time.

Unlike a typical spectrogram obtained using STFT-method  and unlike FFT method the
Heart Energy Signature generates high quality high resolution images that are suitable
for the medical diagnosis.

Typical analysis sequence is presented below:

Step 1:  Visual waveform analysis

1) display heart sound waveform (phonocardiogram- PCG)
2) visualize S1 and S2, systole and diastole (segment heart sound)
3) visualize presence of systolic murmurs, diastolic murmurs, or any heart sounds in
    addition to S1 and S2
4) visualize S2 heart sound and its variation, evaluate for split

Step 2: Frequency Analysis

5) analyze spectral (frequency) properties of murmurs, estimate murmur frequency scores
6) analyze murmur timing and intensity, estimate corresponding scores

Step 3: Heart Energy Signature

7)  visualize and evaluate (normal-abnormal) visual image of the heart energy signature

8)  review heart sound power variation (looks lot like Doppler-echo velocity vs. time plot)  
     to verify signal segmentation and to identify most important (energetic) events
9)  visualize power vs. time plot to document presence of S1 or S2 splits and their
     variation [power plot is the best tool for that]
10) visualize instantaneous (peak, mean) frequency vs. time plot to document pitch
      related abnormalities
11) estimate time averaged murmur frequency characteristics form the energy density  
     spectrum plot [this is best tool for that]

(optional)
12) estimate instantaneous murmur or sound component density spectrum at the point
      of their maximum energy [this shows intrinsic time variation properties]
11) estimate instantaneous power variation with time at the point of murmur
maximum/dominant frequency [shows only power at the pitch of interest]