A novel method to represent ECG signals via predefined personalized signature and envelope functions
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Tarih
2001Yazar
Yarman, Bekir Sıddık Binboğa
Gürkan, Hakan
Güz, Ümit
Aygün, B
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In this paper, a new method to model ECG signals by means of "Predefined Personalized Signature and Envelope Functions" is presented. ECG signals are somewhat unique to a person. Moreover, it presents quasistationary behavior. Therefore in this work, on a frame basis, personal ECG signals Xi(t) is modeled by the form of Xi(t) approximate to C(i)phi(i)(t) alpha(i)(t). In this model, phi(i)(t) is defined as the Personalized Signature Function (PSF); alpha(i)(t) is referred to as Personalized Envelope Function (PEF) and Ci is called the FrameScaling Coefficient (FSC). It has been demonstrated that for each person, the sets Phi = {phi(k)(t)} and A = {alpha(r)(t)} constitute a "Predefined Personalized Functional Bases or Banks (PPFB)" to describe any measured ECG signal. Almost optimum forms of (PPFB), namely {alpha(r)(t)}, {phi(k)(t)} pairs are generated in the Least Mean Square (LMS) sense. Thus, ECG signal for each frame is described in terms of the two indices "R" and "K" of PPFB and the framescaling coefficient Ci. It has been shown that the new method of modeling provides significant data compression. Furthermore, once PPFB are stored on each communication node, transmission of ECG signals reduces to the transmission of indexes "R" and "K" of pairs and the coefficients Ci, which also result in considerable saving in the transmission band.
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