title: Several insights into the preprocessing of electrograms in atrial fibrillation for dominant frequency analysis.
abstract: BACKGROUND
  Dominant frequency (DF) analysis of atrial electrograms has become an important method in characterizing atrial fibrillation (AF). As a classic method, Botteron's approach is widely used in the preprocessing of frequency analysis during AF. It includes three steps: (1) band-pass filtering at 40-250 Hz, (2) absolute value, and (3) low-pass filtering at 20 Hz. This paper aims to expound the necessity and adjustability of each step.
  
  
  RESULTS
  Unipolar epicardial mapping signals were recorded during AF from eight mongrel dogs with cholinergic AF model. Episodes of these data were randomly selected to evaluate the impact of different pass bands and the necessity of low-pass filtering with 20 Hz cutoff frequency. Each episode of AF signal is 5 s long with a sampling rate of 2 kHz. Simulated electrograms were adopted to discuss the role of taking absolute value. Furthermore, direct spectral analysis method (FFT et al.) is compared with Botteron's preprocessing approach. According to our statistical analysis, the pass band of 40-250 Hz was not the best, while 20-100 Hz presented the high accuracy rate of DF. From the comparing result of direct FFT without Botteron's approach we deduced that the rectification of absolute value was meaningful for the fundamental atrial frequency. The final step, 20 Hz low-pass filter can completely be omitted in DF analysis. In consideration of the demand for real-time distribution of DF in clinical or experimental situations, down-sampling method and the impact of ventricular artifacts on DF was also discussed.
  
  
  CONCLUSIONS
  In the actual application of the three preprocessing steps, the pass band selection of band-pass filter can be adjusted and the rectification of taking absolute value is important. Nevertheless, the final step of 20 Hz low-pass filter is totally unnecessary. In real-time signal processing situations, taking down-sampling method and ignoring the ventricular artifacts can also have high performance in DF analysis of atrial electrograms.
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
authors.forename: Wenhai
authors.initials: W
authors.lastname: Li
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China. yangcw@fudan.edu.cn.|Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, 200433, China. yangcw@fudan.edu.cn.|Shanghai Engineering Research Center of Assistive Devices, Shanghai, 200433, China. yangcw@fudan.edu.cn.
authors.forename: Cuiwei
authors.initials: C
authors.lastname: Yang
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
authors.forename: Yanlei
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
authors.forename: Dexi
authors.initials: D
authors.lastname: Wang
authors.affiliation: Department of Electronic Science and Engineering, Nanjing University, Nanjing, 210046, Jiangsu, China.
authors.forename: Ying
authors.initials: Y
authors.lastname: Chen
authors.affiliation: Department of Cardiovascular Surgery, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.
authors.forename: Zhong
authors.initials: Z
authors.lastname: Wu
mesh_terms: D000818:Animals; D001281:Atrial Fibrillation / Q000175:diagnosis*; D004285:Dogs; D022062:Electrophysiologic Techniques, Cardiac / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors
keywords: Atrial fibrillation; Dominant frequency; Down-sampling; Electrograms; Preprocessing