Power Spectral Estimation of short-term AF Recordings by Parametric Method Based on AR Model
Pages 112 - 116
Abstract
With the aggravation of population aging, the number of atrial fibrillation (AF) has increased dramatically, seriously endangering human health. Therefore, in order to detect AF on wearable devices accurately, parametric power spectrum estimation (PSD) based on autoregressive (AR) model was used to extract and analyze the frequency-domain features of short-term AF recordings. By comparing classical PSD with parameter PSD based on AR model for short-term AF signals with baseline wandering removed, it was found that this algorithm can estimate real signals, and the PSD results of AF signals and sinus rhythm signals are distinct. Moreover, the influence of model order for PSD was analyzed. Simulation results show that the parametric PSD based on AR model can accurately extract the frequency-domain characteristics of AF signals and is an effective method.
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Index Terms
- Power Spectral Estimation of short-term AF Recordings by Parametric Method Based on AR Model
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Published In
September 2020
313 pages
ISBN:9781450388603
DOI:10.1145/3429889
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Association for Computing Machinery
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Published: 04 December 2020
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ISAIMS 2020
ISAIMS 2020: 2020 International Symposium on Artificial Intelligence in Medical Sciences
September 11 - 13, 2020
Beijing, China
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ISAIMS '20 Paper Acceptance Rate 53 of 112 submissions, 47%;
Overall Acceptance Rate 53 of 112 submissions, 47%
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