A Novel Method to Represent ECG Signals Via Predefined Personalized Signature and Envelope Functions
Abstract
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 quasi-stationary behavior. Therefore in this work, on a frame basis, personal ECG signals X(sub i)(t) is modeled by the form of X(sub i)(t) = C(sub i)phi(sub i)(t) alpha(sub i)(t). In this model, phi(sub i)(t) is defined as the Personalized Signature Function (PSF); alpha(sub i)(t) is referred to as Personalized Envelope Function (PEF) and C(sub i) is called the Frame-Scaling Coefficient (FSC). It has been demonstrated that for each person, the sets Phi=?phi(sub k)(t)! and Alpha=?alpha(sub r)(t)! constitute a "Predefined Personalized Functional Bases or Banks (PPFB)" to describe any measured ECG signal. Almost optimum forms of (PPFB), namely ?alpha(sub r)(t)!, ?phi(sub 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 frame-scaling coefficient C(sub i). 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 ALPHA(SUB R)(T), PHI(SUB K)(T) pairs and the coefficients C(sub i), which also result in considerable saving in the transmission band.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 25, 2001
- Accession Number
- ADA411176
Entities
People
- B. Aygun
- B. S. Yarman
- H. Gurkan
- U. Guz
Organizations
- Işık University