Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/105984
Type: Artigo de evento
Title: Oropharyngeal Dysphagia Identification Using Wavelets And Optimum Path Forest
Author: Spadotto A.A.
Pereira J.C.
Guido R.C.
Papa J.P.
Falcao A.X.
Gatto A.R.
Cola P.C.
Schelp A.O.
Abstract: The swallowing disturbers are defined as oropharyngeal dysphagia when present specifies signals and symptoms that are characterized for alterations in any phases of swallowing. Early diagnosis is crucial for the prognosis of patients with dysphagia and the potential to diagnose dysphagia in a noninvasive manner by assessing the sounds of swallowing is a highly attractive option for the dysphagia clinician. This study proposes a new framework for oropharyngeal dysphagia identification, having two main contributions: a new set of features extract from swallowing signal by discrete wavelet transform and the dysphagia classification by a novel pattern classifier called OPF. We also employed the well known SVM algorithm in the dysphagia identification task, for comparison purposes. We performed the experiments in two sub-signals: the first was the moment of the maximal peak (MP) of the signal and the second is the swallowing apnea period (SAP). The OPF final accuracy obtained were 85.2% and 80.2% for the analyzed signals MP and SAP, respectively, outperforming the SVM results. ©2008 IEEE.
Editor: 
Rights: fechado
Identifier DOI: 10.1109/ISCCSP.2008.4537320
Address: http://www.scopus.com/inward/record.url?eid=2-s2.0-50649108366&partnerID=40&md5=111edb38ee340254e9dc52b15cfc34cf
Date Issue: 2008
Appears in Collections:Unicamp - Artigos e Outros Documentos

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