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Summary: Atrial Fibrillation Analysis using Bessel Kernel based Time Frequency
Distribution Technique
Sandun Kodituwakku, Thushara D. Abhayapala, Rodney A. Kennedy
Research School of Information Sciences and Engineering
The Australian National University, Australia
Abstract
We propose a Bessel kernel based time frequency distri-
bution technique for identification and tracking of spec-
trum of Atrial Fibrillation (AF) in ECG. The algorithm
shows a good frequency resolution and a low RMS error
even when the noise dominates the signal which is criti-
cal for detecting the low amplitude AF activity within the
ECG. In comparison with other time frequency distribu-
tions, the Bessel kernel reduces cross terms between fre-
quencies in the multi-component ECG signal. Superiority
of the Bessel kernel method over the short time Fourier
transform (STFT) is demonstrated using a frequency mod-
ulated sinusoidal model and using real AF data. At low
signal to noise levels the Bessel distribution outperforms
the STFT and at an SNR of -5dB the RMS error is reduced
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