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Caracterización de sonidos deglutorios adquiridos mediante auscultación cervical en sujetos sanos y con disfagia.

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dc.contributor.authorBetancur Rengifo, Juan Pablospa
dc.contributor.authorRestrepo Uribe, Juan Pablospa
dc.contributor.authorPérez Giraldo, Estefaniaspa
dc.contributor.authorOrozco Duque, Andrésspa
dc.date.accessioned2022-06-01 00:00:00
dc.date.accessioned2022-06-17T20:21:40Z
dc.date.available2022-06-01 00:00:00
dc.date.available2022-06-17T20:21:40Z
dc.date.issued2022-06-01
dc.description.abstractLa deglución es un acto de alta complejidad neuromuscular debido a que intervienen más de 30 pares musculares y 5 pares craneales en un periodo corto de tiempo. Esta se divide en 4 etapas: pre oral, oral, orofaríngea y esofágica, una alteración en el desarrollo normal de alguna de estas fases puede desarrollar un síntoma secundario a enfermedades neuromusculares y neurogénicas que se conoce como disfagia, esta puede traer consigo muchas dificultades para quien la padece, entre esta neumonía bronquial, desnutrición, deshidratación o incluso la muerte por asfixia. La identificación de características que ayuden a reconocer dicho síntoma, además de describir correctamente el proceso deglutorio, es de gran importancia ya que los métodos existentes son invasivos. La auscultación cervical es una técnica mediante la cual se puede obtener información del cierre glótico en el proceso deglutorio por medio de señales de audio, y que puede ser analizada de manera off line. El objetivo de este estudio es evaluar diferentes métodos de caracterización de señales de auscultación cervical y desarrollar un modelo de aprendizaje automático con sonidos de eventos deglutorios segmentados de forma manual para clasificar entre sujetos de control y pacientes con disfagia orofaríngea. Los resultados mostraron, con una exactitud máxima de 75 %, que por medio de señales de auscultación cervical es posible identificar sujetos con disfagia, de igual manera se logró identificar que la potencia media de los segmentos deglutorios fue la característica con mejor rendimiento (curva ROC) y una distribución diferente entre clases según la prueba de U-Mann-Whitney, para discriminar entre sanos y pacientes en diferentes actividades deglutorias.spa
dc.description.abstractSwallowing is an act of high neuromuscular complexity due to the involvement of more than 30 muscle pairs and 5 cranial pairs that occurs in a short period of time. This activity is divided into 4 stages: pre-oral, oral, oropharyngeal and esophageal, an alteration in the normal development of this process can develop a symptom secondary to neuromuscular and neurogenic diseases that is known as dysphagia. Dysphagia can bring many difficulties for those who suffer from it including bronchial pneumonia, malnutrition, dehydration or even death by asphyxia. The identification of characteristics that help recognize this symptom, in addition to correctly describing the swallowing process is of great importance since the existing methods are invasive. Cervical auscultation is a technique by which information about the gothic closure can be obtained in the swallowing process using audio signals, and which can be analyzed offline. The aim of this study is to evaluate different methods of characterization of cervical auscultation signals and develop a machine learning model with manually segmented swallowing event sounds to classify between control subjects and patients with oropharyngeal dysphagia. The results showed, with a maximum accuracy of 75% that by means of signs is cervical auscultation it is possible to identify dysphageal subjects. In the same way it was possible to identify that the average potency of the swallowing segments was the feature with the best score (ROC curve) and that exists a different distribution between classes in this characteristic according to the U-Mann-whitney test to discriminate between healthy and pathologic subjects during different swallowing activities.eng
dc.format.mimetypeapplication/pdfspa
dc.identifier.doi10.24050/reia.v19i38.1579
dc.identifier.eissn2463-0950
dc.identifier.issn1794-1237
dc.identifier.urihttps://repository.eia.edu.co/handle/11190/5188
dc.identifier.urlhttps://doi.org/10.24050/reia.v19i38.1579
dc.language.isospaspa
dc.publisherFondo Editorial EIA - Universidad EIAspa
dc.relation.bitstreamhttps://revistas.eia.edu.co/index.php/reveia/article/download/1579/1484
dc.relation.citationeditionNúm. 38 , Año 2022 : .spa
dc.relation.citationendpage12
dc.relation.citationissue38spa
dc.relation.citationstartpage3831 pp. 1
dc.relation.citationvolume19spa
dc.relation.ispartofjournalRevista EIAspa
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dc.rightsRevista EIA - 2022spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa
dc.rights.creativecommonsEsta obra está bajo una licencia internacional Creative Commons Atribución-NoComercial-SinDerivadas 4.0.spa
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0spa
dc.sourcehttps://revistas.eia.edu.co/index.php/reveia/article/view/1579spa
dc.subjectAuscultación cervicalspa
dc.subjectclasificaciónspa
dc.subjectdisfagiaspa
dc.subjectextracción de característicasspa
dc.subjectprocesamiento de señalesspa
dc.subjectexactitudspa
dc.subjectrendimientospa
dc.subjectdificultadesspa
dc.subjectinvasivosspa
dc.subjectaprendizaje de máquinaspa
dc.subjectCervical auscultationeng
dc.subjectclassificationeng
dc.subjectdysphagiaeng
dc.subjectfeature extractioneng
dc.subjectsignal processingeng
dc.subjectaccuracyeng
dc.subjectscoreeng
dc.subjectdifficultieseng
dc.subjectinvasiveeng
dc.subjectmachine learningeng
dc.titleCaracterización de sonidos deglutorios adquiridos mediante auscultación cervical en sujetos sanos y con disfagia.spa
dc.title.translatedCharacterization of swallowing sounds through Cervical Auscultation in healthy and dysphagic subjects.eng
dc.typeArtículo de revistaspa
dc.typeJournal articleeng
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTREFspa
dc.type.versioninfo:eu-repo/semantics/publishedVersionspa
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