|Table of Contents|

Optimum heart sound signal selection based on the similarity of power spectral density(PDF)

《中国医学物理学杂志》[ISSN:1005-202X/CN:44-1351/R]

Issue:
2022年第11期
Page:
1401-1406
Research Field:
医学信号处理与医学仪器
Publishing date:

Info

Title:
Optimum heart sound signal selection based on the similarity of power spectral density
Author(s):
WANG Jiaming1 ZHANG Anqi2 HAO Hongyan1 WANG Chunyun1 CHEN Si2
1. Procurement Center, Nanjing Drum Tower Hospital, the Affiliated Hospital of Nanjing University Medical School, Nanjing 210008, China 2. National Research Center of Pumps and Pumping System Engineering Technology, Jiangsu University, Zhenjiang 212013, China
Keywords:
Keywords: optimum heart sound signal automated heart sound selection quality index wavelet transform power spectral density similarity
PACS:
R318
DOI:
DOI:10.3969/j.issn.1005-202X.2022.11.013
Abstract:
Abstract: Heart sound (HS) diagnosis is affected by interference noise mixed in the process of HS recording. HS signal segments with less interference are often selected manually for subsequent analysis at present. A novel method for automatically selecting the optimum HS signal with minimum interference and maximum stability from the collected HS signal is presented. The cardiac cycles of 25 healthy children and 119 children with congenital heart disease are located using discrete wavelet transform combined with Hadamard product. Quality index is calculated according to the cycle stability and power spectral density similarity of cardiac cycle signal, and the 3 consecutive cardiac cycle signals with maximum quality index are taken as the optimum HS signal. The success rate and effectiveness of signal selection are evaluated by the cardiologist through audio playback. The results show that the success rate of optimum HS signal selection is 95.83%, and that the selected signal contains the typical auscultation characteristics of the corresponding diseases. In conclusion, the proposed method has good performance and executes the HS signal selection automatically, providing a reference for the fully automatic analysis of HS signal.

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Last Update: 2022-11-25