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Autoencoder를 이용한 음성 신호 기반의 연하장애 검출 기법

Other Titles
 Speech Signal based Dysphagia Detection using Autoencoder 
Authors
 강상익  ;  조경일  ;  금명철  ;  서경천  ;  박윤길  ;  박진영  ;  차은실  ;  정석영  ;  이주강  ;  유제현  ;  최경효 
Citation
 Journal of Rehabilitation Welfare Engineering & Assistive Technology(재활복지공학회논문지), Vol.16(1) : 13-18, 2022-02 
Journal Title
Journal of Rehabilitation Welfare Engineering & Assistive Technology(재활복지공학회논문지)
ISSN
 1976-7102 
Issue Date
2022-02
Keywords
Dysphagia ; Autoencoder ; Anomaly detection ; VFSS ; Voice-based diagnosis
Abstract
n this paper, a novel approach is proposed to improve speech-based dysphagia detection using an autoencoder. The water swallow test using voice is a convenient test method but has a problem due to low accuracy. Based on the /a/ voice data before and after the VFSS(Video Fluoroscopic Swallowing Study) test, which is a representative method for examining dysphagia, an autoencoder with a strong performance in detecting abnormalities is used to determine dysphagia. Data from 33 normal subjects were used for training. In 16 normal subjects and 39 patients with dysphagia, the proposed algorithm yields 23%p higher performance compared with the conventional Praat based scheme.
Full Text
https://www.dbpia.co.kr/journal/articleDetail?nodeId=NODE11038948
DOI
10.21288/resko.2022.16.1.13
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Rehabilitation Medicine (재활의학교실) > 1. Journal Papers
Yonsei Authors
Park, Yoon Ghil(박윤길) ORCID logo https://orcid.org/0000-0001-9054-5300
Park, Jinyoung(박진영) ORCID logo https://orcid.org/0000-0003-4042-9779
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/193780
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