Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition

Abstract: Auscultation methods allow a non-invasive diagnosis of cardiovascular diseases like atherosclerosis based on blood flow sounds of the carotid arteries. Since this process is highly dependent on the clinician’s experience, it is of great interest to develop automated data processing techniques for objective assessment. We have recently proposed a computerassisted auscultation system that we use to acquire carotid blood flow sounds. In this work, we present an approach for detecting artifacts within the blood flow sound caused by swallowing or coughing events. For this purpose, we first decompose the signal using a discrete wavelet transform (DTW). Then, we compute an energy ratio between the DWT scales associated with the signal information with and without artifacts using a sliding window of 1 s length. Evaluation based on Kruskal-Wallis and Wilcoxon rank-sum tests shows a statistically significant difference (p-value<.0001) between the signal with and without artifact. Therefore, the proposed method allows the identification of the studied signal artifacts.

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch

Erschienen in
Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition ; volume:7 ; number:2 ; year:2021 ; pages:299-302 ; extent:4
Current directions in biomedical engineering ; 7, Heft 2 (2021), 299-302 (gesamt 4)

Urheber
Fuentealba, Patricio
Salvi, Rutuja
Henze, Jasmin
Burmann, Anja
Boese, Axel
Ataide, Elmer
Spiller, Moritz
Illanes, Alfredo
Friebe, Michael

DOI
10.1515/cdbme-2021-2076
URN
urn:nbn:de:101:1-2022101214222056451077
Rechteinformation
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Letzte Aktualisierung
15.08.2025, 07:30 MESZ

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Beteiligte

  • Fuentealba, Patricio
  • Salvi, Rutuja
  • Henze, Jasmin
  • Burmann, Anja
  • Boese, Axel
  • Ataide, Elmer
  • Spiller, Moritz
  • Illanes, Alfredo
  • Friebe, Michael

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