The coherence spectrum. A quantitative discriminator of fibrillatory and nonfibrillatory cardiac rhythms.

Abstract

Previous work has suggested that a comparison of electrograms from two or more sites may best differentiate fibrillatory from nonfibrillatory rhythms. The coherence spectrum is a measure by which two signals may be compared quantitatively in the frequency domain. In the present study, the coherence spectrum was used to quantify the relation between spectral components of electrograms from two sites in either the atrium or ventricle during both fibrillatory and nonfibrillatory rhythms. Bipolar recordings of 35 rhythms from 20 patients were analyzed for coherence in the 1-59 Hz band. The 17 nonfibrillatory rhythms were sinus rhythm (six), paroxysmal supraventricular tachycardia (two), atrial flutter (four), and monomorphic ventricular tachycardia (five). The 18 fibrillatory rhythms were atrial fibrillation (12) and ventricular fibrillation (six). Nonfibrillatory rhythms exhibited moderate-to-high levels of coherence throughout the 1-59 Hz band, with peaks concentrated at the rhythm's fundamental frequency and its harmonics. Fibrillatory rhythms exhibited little coherence throughout the 1-59 Hz band, and harmonics were not evident. The mean magnitude-squared coherence (scale of 0 to 1) for the 1-59 Hz band ranged from 0.22 to 0.86 (mean± SD, 0.52 ±0.19) for nonfibrillatory rhythms and from 0.042 to 0.12 (0.067±0.021) for fibrillatory rhythms. Separation of fibrillatory and nonfibrillatory rhythms was possible whether signals were recorded by floating or fixed-electrode configurations. These findings indicate that comparison of two electrograms with magnitude-squared coherence measurements differentiates fibrillatory from nonfibrillatory rhythms. A recognition algorithm based on coherence spectra may be robust in the face of major variations in lead configuration. Furthermore, the coherence spectra may provide a means to quantify the "organization" or "disorganization" of a cardiac rhythm. (Circulation 1989;80:112-119) F ibrillatory rhythms are typically described as "chaotic" and "disorganized." More specifically, the activity from multiple sites during fibrillation has been described as asynchronous and incoordinate.1-6 Allessie et a16 have suggested that the comparison of activity from two or more sites may best differentiate fibrillatory from nonfibrillatory rhythms. While this "altered spatial arrangement of conduction"7 is quintessential to fibrillation, this qualitative characteristic remains to be quantified. Previous studies have used frequencyFrom the

Multiple domain evaluation of watershed hydrology models

“…The magnitude squared coherence approach is used to compare the frequency content of measured and simulated signals and provides a measure of their similarity (Ropella et al, 1989). The technique captures all the frequencies 25 present in the analyzed signal without localizing the frequency.…”

Ventricular activity cancellation in electrograms during atrial fibrillation with constraints on residuals’ power

“…AF organization can be described in terms of various characteristics of electrical activity of the fibrillating atria, such as the repeatability/regularity of the atrial activations [4][5][6], the correlation/synchronicity among electrograms recorded in different locations [7][8][9], or the similarity of the wave morphology [10].…”

Signal processing of intracardiac recordings for the evaluation of propofol effects during atrial fibrillation.

“…Since a rigorous definition of organization does not exist, various approaches have been adopted including frequency analysis [8,9], cross-correlation techniques [10], linear prediction [11], nonlinear analysis [12], as well as signal morphology [13].…”

“…The challenge is to develop methods suitable for quantifying the extent of spatial organization during AF, from the analysis of a single electrogram [16], and from the combined analysis of multiple atrial recordings that may provide more comprehensive information [10,9].…”

“…If the atrial signal is highly periodic, the dominant frequency will in most cases be related to the rate of the signal. Most studies have shown that dominant frequencies generally fall within a range of 4-9 Hz (240-540 cycles/minute) with narrow band characteristics [9], and are accompanied by several harmonics with lower peak amplitude finding suggest that AF is not completely chaotic. In addition, other different electrocardiographic approaches may be useful in the clinical management of patients with AF.…”