Short-Time Fourier transforms, Wigner-Ville distribution, and Wavelet Transforms have been commonly used when dealing with non-stationary signals, and they have been known as time-frequency distributions. Also, it is commonly intended to investigate the behaviour of phonocardiogram signals as a means of prediction some oh the pathologies of the human hart. For this, this paper aims to analyze the relationship between the instantaneous frequency of a PCG signal and the so-mentioned time-frequency distributions; three algorithms using Matlab functions have been developed: the first one, the estimation of the IF using the normalized linear moment, the second one, the estimation of the IF using the periodic first moment, and the third one, the computing of the WVD. Meanwhile, the computing of the STFT spectrogram is carried out with a Matlab function. Several simulations of the spectrogram for a set of PCG signals and the estimation of the IF are shown, and its relationship is validated through correlation. Finally, the second algorithm is a better choice because the estimation is not biased, whereas the WVD is very computing-demanding and offers no benefit since the estimation of the IF by using this TFD has an equivalent result when using the derivative of the phase of the analytic signal, which is also less computing-demanding.
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