Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition
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 ob...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2021-10-01
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| Series: | Current Directions in Biomedical Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/cdbme-2021-2076 |
| _version_ | 1797989329109254144 |
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| author | Fuentealba Patricio Salvi Rutuja Henze Jasmin Burmann Anja Boese Axel Ataide Elmer Spiller Moritz Illanes Alfredo Friebe Michael |
| author_facet | Fuentealba Patricio Salvi Rutuja Henze Jasmin Burmann Anja Boese Axel Ataide Elmer Spiller Moritz Illanes Alfredo Friebe Michael |
| author_sort | Fuentealba Patricio |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T08:17:21Z |
| format | Article |
| id | doaj.art-da5854cffc9e4aafb4140b435c7ff71d |
| institution | Directory Open Access Journal |
| issn | 2364-5504 |
| language | English |
| last_indexed | 2024-04-11T08:17:21Z |
| publishDate | 2021-10-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Current Directions in Biomedical Engineering |
| spelling | doaj.art-da5854cffc9e4aafb4140b435c7ff71d2022-12-22T04:35:04ZengDe GruyterCurrent Directions in Biomedical Engineering2364-55042021-10-017229930210.1515/cdbme-2021-2076Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform DecompositionFuentealba Patricio0Salvi Rutuja1Henze Jasmin2Burmann Anja3Boese Axel4Ataide Elmer5Spiller Moritz6Illanes Alfredo7Friebe Michael8IDTM GmbH, Recklinghausen, Germany + Instituto de Electricidad y Electrónica, Facultad de Ciencias de la Ingeniería, Universidad Austral de Chile,Valdivia, ChileIDTM GmbH,Recklinghausen, GermanyFraunhofer Institute for Software and Systems Engineering,Dortmund, GermanyFraunhofer Institute for Software and Systems Engineering,Dortmund, GermanyHealthTec Innovation Laboratory, Otto-von-Guericke-University + MEDICS GmbH,Magdeburg, GermanyDivision of Nuclear Medicine Department of Radiology + INKA - Application Driven Research Innovation Laboratory, Otto-von-Guericke University,Magdeburg, GermanyHealthTec Innovation Laboratory, Surgical Audio Guidance, Otto-von-Guericke-University,Magdeburg, GermanyHealthTec Innovation Laboratory, Surgical Audio Guidance, Otto-von-Guericke-University,Magdeburg, GermanyHealthTec Innovation Laboratory, Otto-von- Guericke-University, Magdeburg + IDTM GmbH,Recklinghausen, GermanyAuscultation 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.https://doi.org/10.1515/cdbme-2021-2076carotid sounddiscrete wavelet transform |
| spellingShingle | Fuentealba Patricio Salvi Rutuja Henze Jasmin Burmann Anja Boese Axel Ataide Elmer Spiller Moritz Illanes Alfredo Friebe Michael Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition Current Directions in Biomedical Engineering carotid sound discrete wavelet transform |
| title | Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition |
| title_full | Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition |
| title_fullStr | Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition |
| title_full_unstemmed | Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition |
| title_short | Carotid Sound Signal Artifact Detection based on Discrete Wavelet Transform Decomposition |
| title_sort | carotid sound signal artifact detection based on discrete wavelet transform decomposition |
| topic | carotid sound discrete wavelet transform |
| url | https://doi.org/10.1515/cdbme-2021-2076 |
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