Literature DB >> 25570924

Detection of Obstructive sleep apnea in awake subjects by exploiting body posture effects on the speech signal.

M Kriboy, A Tarasiuk, Y Zigel.   

Abstract

Obstructive sleep apnea (OSA) is a common sleep disorder. OSA is associated with several anatomical and functional abnormalities of the upper airway. It was shown that these abnormalities in the upper airway are also likely to be the reason for increased rate of apneic events in the supine position. Functional and structural changes in the vocal tract can affect the acoustic properties of speech. We hypothesize that acoustic properties of speech that are affected by body position may aid in distinguishing between OSA and non-OSA patients. We aimed to explore the possibility to differentiate OSA and non-OSA patients by analyzing the acoustic properties of their speech signal in upright sitting and supine positions. 35 awake patients were recorded while pronouncing sustained vowels in the upright sitting and supine positions. Using linear discriminant analysis (LDA) classifier, accuracy of 84.6%, sensitivity of 92.7%, and specificity of 80.0% were achieved. This study provides the proof of concept that it is possible to screen for OSA by analyzing and comparing speech properties acquired in upright sitting vs. supine positions. An acoustic-based screening system during wakefulness may address the growing needs for a reliable OSA screening tool; further studies are needed to support these findings.

Entities:  

Mesh:

Year:  2014        PMID: 25570924     DOI: 10.1109/EMBC.2014.6944556

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Reviewing the connection between speech and obstructive sleep apnea.

Authors:  Fernando Espinoza-Cuadros; Rubén Fernández-Pozo; Doroteo T Toledano; José D Alcázar-Ramírez; Eduardo López-Gonzalo; Luis A Hernández-Gómez
Journal:  Biomed Eng Online       Date:  2016-02-20       Impact factor: 2.819

2.  Speech Signal and Facial Image Processing for Obstructive Sleep Apnea Assessment.

Authors:  Fernando Espinoza-Cuadros; Rubén Fernández-Pozo; Doroteo T Toledano; José D Alcázar-Ramírez; Eduardo López-Gonzalo; Luis A Hernández-Gómez
Journal:  Comput Math Methods Med       Date:  2015-11-17       Impact factor: 2.238

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.