No abstract

We propose the calculation of the heart instantaneous frequency (HIF) from an estimate of the spectrogram of the weights obtained by LMS algorithm, when implemented as a spectrum analyzer. One knows that the electrocardiogram (ECG) is characterized for its repetitive regularity, that we can call quasiperiodicity. We explore this characteristic to extract the heart instantaneous frequency of the related signal. For this, we use the LMS as a spectrum analyzer. The algorithm estimates the desired frequency in real time, with the data acquisition performed by the Intel data interface 80C31. The obtained results shown that the algorithm can be recommended for this purpose, because the system is easily implementable, generates small computational load besides estimate the heart instantaneous frequency with an average relative error of 0.025, that represents a difference of 18.89% between the used methodology and wavelets transform (WT).

The Least Mean Square (LMS) algorithm is a very important tool in the estimation and filtering of biomedical signals. Amongst these signals are the periodic and quasiperiodic. For example, the LMS algorithm was used to estimate the coefficients of the Fourier series at a given frequency or even in a spectral analysis. In this paper we study the behavior of the weights of the LMS algorithm when the signal to be estimated acts at very low frequencies. We prove theoretically that lower frequency noise affects the estimation of the weights at higher frequencies. We carried out simulations and showed that experimental findings are in agreement with the theoretical results. Moreover, we exemplify the problem with electrocardiogram signals (ECG).