New algorithm for the detection of the ECG fiducial point in the averaging technique

Abstract

The use of the coherent averaging technique applied to the electrocardiographic signal implies the location of a fiducial point as a synchronisation reference. An algorithm easily adaptable to a personal computer, operable in real time, insensitive to mains and to ECG-baseline fluctuations, with a low jitter value and the capacity to trigger any ECG signal wave or complex, has been developed. The algorithm detects those waveforms which, within certain confidence intervals, are morphologically equal to a reference wave. This wave is chosen by the user as the repetitive waveform within which the fiducial point is to be located. A two-window template and differential parameters are used. The possibility of building the template permits the user to adapt the algorithm to each patient's ECG. To evaluate its accuracy objectively, a software simulation was built of a generator capable of producing test signals as the sum of the 'useful' signal plus 'noise'. A jitter standard deviation of 1.65 ms was obtained in the worst test (SNR = 10 dB; noiseband = 0-50 Hz), which shows the excellent recognition accuracy of the algorithm.

Influence of Age, Lead Axis, Frequency of Arrhythmic Episodes, and Atrial Dimensions on P Wave Triggered SAECG in Patients with Lone Paroxysmal Atrial Fibrillation

“…(2) age conditions atrial electrophysiological behavior and must be taken into account when evaluating signal-averaged P wave; (3) some orthogonal leads seem more able than others to demonstrate the existence of a pathopbysiological condition; (4) frequency analysis should be performed on the entire P wave; (5) frequency content of a lead varies according to its spatial location; (6) greater right and left atrial dimensions, even if within the range of normal limits, underlie a higher frequency of atrial fibrillation attacks; and (7) tbe major frequency content of signal-averaged P wave (three orthogonal leads) is under 50 Hz.…”

Sampling rate and the estimation of ensemble variability for repetitive signals

“…Several other methods for time alignment of QRS complexes have been presented in the literature. For example, the normalised integral method which estimates the delay between two signals by their normalised integral difference (LAGUNA et al, 1994), the sliding window method in which waveform slopes with opposite signs are detected (BARBARO et al, 1991), or simple threshold crossing detection (JANI~ et al, 1991 ). Since the performance of all three methods were, in general, inferior to that of the Woody method (LAGUNA et al, 1997), the present paper considers only the Woody method for time alignment.…”

Time‐Domain and Morphological Analysis of the P‐Wave. Part I: Technical Aspects for Automatic Quantification of P‐Wave Features

“…This alignment algorithm minimizes the difference between the areas of two rectangular windows, having different mean slopes and selected on the current averaged wave, and the incoming wave (two window minimization, TWM). In this algorithm two‐step procedure is performed 22 . In the prerunning phase two rectangular windows having different mean slopes are manually selected on the reference wave (i.e., the current template) by means of four cursors (Fig.…”