Aplicación de técnicas de clustering en sonidos adventicios para mejorar la interpretabilidad y detección de estertores

Application of clustering techniques for lung sounds to improve interpretability and detection of crackles

dc.creatorSosa, Germán D
dc.creatorVelásquez Clavijo, Fabián
dc.date2018-11-20T23:36:40Z
dc.date2018-11-20T23:36:40Z
dc.date2015-01-05
dc.date.accessioned2023-10-03T19:38:11Z
dc.date.available2023-10-03T19:38:11Z
dc.identifierSosa Ramírez, G., & Velásquez Clavijo, F. (2015). Aplicación de Técnicas de Clustering en Sonidos Adventicios para Mejorar la Interpretabilidad y Detección de Estertores. INGE CUC, 11(1), 53-62. Recuperado a partir de https://revistascientificas.cuc.edu.co/ingecuc/article/view/366
dc.identifier0122-6517, 2382-4700 electrónico
dc.identifierhttp://hdl.handle.net/11323/1564
dc.identifierhttps://doi.org/10.17981/ingecuc.11.1.2015.05
dc.identifier10.17981/ingecuc.11.1.2015.05
dc.identifier2382-4700
dc.identifierCorporación Universidad de la Costa
dc.identifier0122-6517
dc.identifierREDICUC - Repositorio CUC
dc.identifierhttps://repositorio.cuc.edu.co/
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9170904
dc.descriptionDue to the subjectivity involved currently in pulmonary auscultation process and its diagnostic to evaluate the condition of respiratory airways, this work pretends to evaluate the performance of clustering algorithms such as k-means and DBSCAN to perform a computational analysis of lung sounds aiming to visualize a representation of such sounds that highlights the presence of crackles and the energy associated with them. In order to achieve that goal, Wavelet analysis techniques were used in contrast to traditional frequency analysis given the similarity between the typical waveform for a crackle and the wavelet sym4. Once the lung sound signal with isolated crackles is obtained, the clustering process groups crackles in regions of high density and provides visualization that might be useful for the diagnostic made by an expert. Evaluation suggests that k-means groups crackle more effective than DBSCAN in terms of generated clusters.
dc.descriptionDebido a la subjetividad que involucra actualmente el proceso de auscultación pulmonar y su diagnóstico para evaluar la condición de las vías respiratorias de un paciente, este trabajo busca evaluar el desempeño de los algoritmos de clustering: k-means y DBSCAN para efectuar un análisis computacional de sonidos pulmonares con el objetivo de visualizar una representación de dichos sonidos que exalte la presencia de estertores y la energía contenida en ellos. Para este fin, se emplearon técnicas de descomposición y análisis Wavelet a diferencia del tradicional análisis en frecuencia dada la similitud entre la forma de onda de un estertor típico y la wavelet sym4. Obtenida la señal de sonido pulmonar con estertores aislados, el proceso de clustering agrupa estertores en regiones de alta presencia y ofrece una visualización que puede ser de utilidad para el diagnóstico hecho por un experto. La evaluación hecha sugiere que k-means agrupa conjuntos de estertores de forma más efectiva que DBSCAN en términos de clusters generados.
dc.formatapplication/pdf
dc.formatapplication/pdf
dc.languageeng
dc.publisherCorporación Universidad de la Costa
dc.relationINGE CUC; Vol. 11, Núm. 1 (2015)
dc.relationINGE CUC
dc.relationINGE CUC
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dc.relation1
dc.relation11
dc.relationINGE CUC
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.sourceINGE CUC
dc.sourcehttps://revistascientificas.cuc.edu.co/ingecuc/article/view/366
dc.subjectSonido Pulmonar
dc.subjectEstertores
dc.subjectSonidos Vesiculares
dc.subjectSonidos Adventicios
dc.subjectTransformada Wavelet
dc.subjectDescomposición Wavelet
dc.subjectsymlet
dc.subjectClustering
dc.subjectk-means
dc.subjectDBSCAN
dc.subjectlog-ennergy
dc.subjectPulmonary sound
dc.subjectRales
dc.subjectVesicular sounds
dc.subjectAdventitious Sounds  
dc.subjectWavelet Transform
dc.subjectWavelet decomposition
dc.titleAplicación de técnicas de clustering en sonidos adventicios para mejorar la interpretabilidad y detección de estertores
dc.titleApplication of clustering techniques for lung sounds to improve interpretability and detection of crackles
dc.typeArtículo de revista
dc.typehttp://purl.org/coar/resource_type/c_6501
dc.typeText
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typehttp://purl.org/redcol/resource_type/ART
dc.typeinfo:eu-repo/semantics/acceptedVersion
dc.typehttp://purl.org/coar/version/c_ab4af688f83e57aa


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