Key result
Dominant frequencies from 4,096-point Fast Fourier transform analysis of 30-s atrial fibrillation data had the strongest relationship to peak cycle lengths from autocorrelation function analysis.
Observational (n=39)
Autocorrelation function analysis yields peak atrial fibrillation cycle lengths equivalent in value to the dominant frequency obtained from Fast Fourier transform analysis, validating its use in spectral analysis of atrial fibrillation.
Autocorrelation function analysis may offer a valid alternative for atrial fibrillation cycle length assessment; leaves open standardization in clinical electrophysiology.
BACKGROUND: Fast Fourier transform (FFT) analysis is a popular method of spectral analysis of atrial fibrillation cycle lengths (AFCL). Autocorrelation function (ACF) analysis is also available, so the aim of this study was to elucidate the relationship between FFT and ACF analyses in the spectral analysis of AFCLs. METHODS AND RESULTS: A total of 75 atrial fibrillation (AF) data from 39 patients were subjected to analysis. The dominant frequencies (DFs) from 4 different spectral resolutions of the FFT and peak AFCL from the ACF analysis were compared. In the FFT analysis using rectified signals, the DF was influenced by spectral resolution, no matter how the signals were tapered by the Hanning or Hamming window or filtered with the low-pass filter. There was a significant relationship between the DF from each spectral resolution and the peak AFCL. The DF from the 4,096-point FFT analysis had the strongest relationship to the peak AFCL with the smallest difference, when using 30-s AF data. In a study of the different lengths of the atrial fibrillation data, the DF also had a strong correlation to the peak AFCL with a small difference. CONCLUSIONS: The peak AFCL obtained from ACF analysis was not of the same quality as that from FFT analysis, but had the same value as the DF from FFT analysis.
No takes yet. Share an insight, caveat, or question.
Shimizu et al. (2007) conducted an observational in Atrial fibrillation (n=39). Fast Fourier transform (FFT) analysis vs. Autocorrelation function (ACF) analysis was evaluated on Relationship between dominant frequencies from FFT and peak AFCL from ACF. Dominant frequencies from 4,096-point Fast Fourier transform analysis of 30-s atrial fibrillation data had the strongest relationship to peak cycle lengths from autocorrelation function analysis.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: