Literature DB >> 32583274

Voice disorders in severe obstructive sleep apnea patients and comparison of two acoustic analysis software programs: MDVP and Praat.

Mei Wei1,2,3,4,5, Jianqun Du1,2,3,4,5, Xiaoyu Wang1,2,3,4,5, Honghua Lu1,2,3,4,5, Wei Wang6,7,8,9,10, Peng Lin11,12,13,14,15.   

Abstract

OBJECTIVE: The purposes of this study were to explore the effect of obstructive sleep apnea-hypopnea syndrome (OSAHS) on the voice by analyzing the acoustic parameters between patients with OSAHS and those without OSAHS and to compare acoustic analyses performed by two software programs (MDVP and Praat).
METHODS: Patients with OSAHS (n = 75) and normal controls (n = 46) were asked to produce a sustained sound of the vowel /i/ and were analyzed with electroglottography (EGG), MDVP, and Praat software. A self-rated scale (Voice Handicap Index, VHI-10) and acoustic parameters were compared.
RESULTS: There were no statistically significant differences in the fundamental frequency (F0), jitter, shimmer, noise/harmonic ratio (NHR), contact quotient perturbation (CQP), or contact index perturbation (CIP) between the patient group and the normal group. The VHI-10 values were significantly increased in patients with OSAHS. The receiver operating characteristic (ROC) analysis suggested that the shimmer obtained from MDVP and Praat possessed relatively high accuracy in differentiating patients with OSAHS from healthy individuals. The results for F0, jitter, shimmer, and NHR were significantly different between MDVP and Praat in OSAHS patients. In normal persons, there was a significant difference in NHR; however, no significant differences were found for F0, jitter, or shimmer between the two software programs. The results demonstrated that high correlations were found between values obtained by both software programs.
CONCLUSIONS: Patients with OSAHS were prone to vibration irregularity, incomplete glottal closure, hoarseness, and other vocal problems. The two acoustic software programs present different values of acoustic measures. There was a strong correlation and consistency between the parameters calculated by the two software programs.

Entities:  

Keywords:  Acoustic analysis; EGG; MDVP; OSAHS; Praat

Mesh:

Year:  2020        PMID: 32583274      PMCID: PMC7987716          DOI: 10.1007/s11325-020-02102-4

Source DB:  PubMed          Journal:  Sleep Breath        ISSN: 1520-9512            Impact factor:   2.816


  21 in total

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6.  Acoustic changes in voice after surgery for snoring: preliminary results.

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7.  Impact of tonsillectomy with or without adenoidectomy on the acoustic parameters of the voice: a comparative study.

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8.  A fluid-saturated poroelastic model of the vocal folds with hydrated tissue.

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9.  Sleep apnea and 20-year follow-up for all-cause mortality, stroke, and cancer incidence and mortality in the Busselton Health Study cohort.

Authors:  Nathaniel S Marshall; Keith K H Wong; Stewart R J Cullen; Matthew W Knuiman; Ronald R Grunstein
Journal:  J Clin Sleep Med       Date:  2014-04-15       Impact factor: 4.062

10.  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

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  1 in total

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  1 in total

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