Signal-averaged intracardiac electrograms: a new method to detect kent potentials

Changes in P-wave area and P-wave duration after circumferential pulmonary vein isolation

AIMS

The effect of circumferential pulmonary vein isolation (CPVI) on P-wave characteristics is not clear. We used the signal-averaged (SA) electrocardiogram (ECG) and the ECG derived vector cardiogram (dVCG) to study the influence of CPVI on P-wave duration (PWD) and P-wave area (PWA) and studied whether changes were associated with successful outcome after initial CPVI.

METHODS AND RESULTS

Thirty-nine patients (56 +/- 10 years, 72% males) underwent CPVI for paroxysmal or persistent atrial fibrillation (AF). For each patient, an ECG recording was taken at the start and end of the ablation procedure. dVCG was derived using the inverse Dower transform. PWD was defined by manual annotation of earliest onset and latest offset of the SA-P-wave. PWA was calculated as the area under the SA-ECG curve averaged for the 12 ECG leads (PWA-ECG) and SA-dVCG curve (PWA-dVCG). Successful outcome after CPVI was defined as freedom from symptomatic and asymptomatic AF at the end of follow-up (11 +/- 5 months). Average PWD decreased from 132 +/- 14 to 126 +/- 16 ms (P < 0.01). PWA-ECG and PWA-dVCG decreased markedly from 4.64 +/- 1.40 to 3.65 +/- 1.61 mVms (P < 0.001) and from 4.27 +/- 1.66 to 2.48 +/- 1.59 mVms (P < 0.001). Parameters of PWA were not different between successes (n = 31) and failures (n = 8). In contrast, PWD after ablation was significantly shorter in patients with successful outcome (123 +/- 16 vs. 135 +/- 11 ms, P < 0.05).

CONCLUSION

(i) CPVI results in a modest but significant shortening in PWD and a marked decrease in PWA. (ii) PWD was significantly shorter in cases of successful outcome after CPVI.

A novel algorithm for cardiac biosignal filtering based on filtered residue method

In this paper, a new algorithm is presented for the filtering (de-noising) of cardiac bioelectrical signals. The primary target of this algorithm is the class of cardiac action potentials recorded using voltage-sensitive dyes, although the method is also applied to electrocardiographic signals. High periodicity is one of the main features of cardiac biosignals. The proposed algorithm exploits this feature in filtering signals with a minimum amount of distortion. The basic idea is to use signal averaging in time to find the stationary portion of the signal. The residue is found by subtracting the signal average from the corresponding points of the input. After passing through a low-pass filter, the filtered residue (FR) is added back to the signal average to reconstruct the output. The practical implementation of the filter residue algorithm is discussed. Stretching and shrinking operations are the basis for the conversion of quasi-periodic signals into periodic signals, which can then be subjected to the FR algorithm. Various examples are presented, and error estimation is performed to guide the selection of optimal parameters for the algorithm. The ability of the algorithm to reconstruct the variation among beats is demonstrated, and its limitations are discussed.