Numerical Fourier transform spectroscopy of EMG half-waves: fragmentary-decomposition-based approach to nonstationary signal analysis

A nonstationary signal analysis technique is introduced, which regards an o scillatory physiological signal as a sum of its fragments, presented in the form of a fragmentary decomposition (FD). The Virtue of FD is that it is f ree of the necessity to choose a priori the basis functions intended for si gnal analysis or synthesis. FD uses an unchanged signal fragment between ad jacent zero-crossings, as a natural basis function called the half-wave fun ction (HWF). To show that such a function is a physically meaningful object , Fourier transform methods were employed, supported by the similar basis f unction (SBF) algorithm, which provides the means for numerical Fourier tra nsform spectroscopy of separate half-waves and their frequency domain descr iption in terms of both amplitude and phase. The application of this method to parameter identification of 751 EMG half-waves from the eye blink EMG r ecords of ten normal subjects showed that HWF's frequency domain image repr esents a Gaussian distribution, which applies over a defined range of relat ive frequencies. This empirical evidence shows that HWFs are produced by a specific system of first-order nonlinear differential equations, whose depe ndency on a. number of random factors is characteristic of deterministic ch aos. The particular form of solutions indicates that statistical regulariti es relevant to the central limit theorem are likely to underlie the genesis of the mass potentials studied. FD shows potential utility in a range of n onstationary physiological signals.