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Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2018 Apr 25;35(2):161-170. doi: 10.7507/1001-5515.201706096.

[Rhythm analysis of body surface potential mapping recordings from atrial fibrillation patients based on autocorrelation function].

Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi

[Article in Chinese]
Qingzhou Zhang, Cuiwei Yang, Baodan Bai

Affiliations

  1. Department of Electronic Engineering, Fudan University, Shanghai 200433, P.R.China.
  2. Department of Electronic Engineering, Fudan University, Shanghai 200433, P.R.China;Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai 200433, P.R.China;Shanghai Engineering Research Center of Assistive Devices, Shanghai 200093, [email protected].
  3. School of Medical Instrument, Shanghai University of Medicine and Health Sciences, Shanghai 201318, P.R.China.

PMID: 29745519 DOI: 10.7507/1001-5515.201706096

Abstract

The study of atrial fibrillation (AF) has been known as a hot topic of clinical concern. Body surface potential mapping (BSPM), a noninvasive electrical mapping technology, has been widely used in the study of AF. This study adopted 10 AF patients' preoperative and postoperative BSPM data (each patient's data contained 128 channels), and applied the autocorrelation function method to obtain the activation interval of the BSPM signals. The activation interval results were compared with that of manual counting method and the applicability of the autocorrelation function method was verified. Furthermore, we compared the autocorrelation function method with the commonly used fast Fourier transform (FFT) method. It was found that the autocorrelation function method was more accurate. Finally, to find a simple rule to predict the recurrence of atrial fibrillation, the autocorrelation function method was used to analyze the preoperative BSPM signals of 10 patients with persistent AF. Consequently, we found that if the patient's proportion of channels with dominant frequency larger than 2.5 Hz in the anterior left region is greater than the other three regions (the anterior right region, the posterior left region, and the posterior right region), he or she might have a higher possibility of AF recurrence. This study verified the rationality of the autocorrelation function method for rhythm analysis and concluded a simple rule of AF recurrence prediction based on this method.

Keywords: atrial fibrillation; autocorrelation function; body surface potential mapping; fast Fourier transform; rhythm analysis

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