Literature DB >> 31760837

Acoustic analysis of voice in bulbar amyotrophic lateral sclerosis: a systematic review and meta-analysis of studies.

Rita Chiaramonte1, Marco Bonfiglio2.   

Abstract

Objective: A systematic review and a meta-analysis were performed to identify the main characteristics of voice disturbances in bulbar amyotrophic lateral sclerosis.Materials and
Methods: Literature searches with the keywords: "amyotrophic lateral sclerosis" and "dysarthria" and "intelligibility" were conducted in PubMed, EMBASE, Cochrane Library and Web of Science to perform the systematic review about the articulatory disorders and with the keyword "amyotrophic lateral sclerosis" and "voice" to conduct the meta-analysis about the phonetic changes in patients with bulbar ALS.
Results: Seven publications met the inclusion criteria and were included in the meta-analysis, twenty-six publications were included in the systematic review. The data within the meta-analysis revealed that several voice parameters including Jitter, Shimmer, Noise to Harmonic Ratio discriminated best between bulbar amyotrophic lateral sclerosis and healthy controls. On the other hand, significant variations of fundamental frequency were not observed.
Conclusion: Acoustic analysis of voice and articulatory analysis contributes to identification of the earliest signs of bulbar degeneration and allows the identification of changes in voice parameters for an early detection, for predicting bulbar involvement and the worsening of disease, for targeting specific intervention. Among the voice parameters, Jitter and Shimmer discriminated better bulbar involvement, they are significantly increased in the patients, on the contrary maximum phonation time is significantly worsened. The careful monitoring of speech symptoms improves diagnostic accuracy and the close cooperation of a multidisciplinary team (physicians as otolaryngologist and physiatrist, speech and language therapists, physiotherapist, dietitians, caregivers, the patients, and their relatives) could be essential.

Entities:  

Keywords:  Acoustic analysis; diagnosis; speech-language-pathology; voice

Year:  2019        PMID: 31760837     DOI: 10.1080/14015439.2019.1687748

Source DB:  PubMed          Journal:  Logoped Phoniatr Vocol        ISSN: 1401-5439            Impact factor:   1.487


  3 in total

1.  Repeatability of Commonly Used Speech and Language Features for Clinical Applications.

Authors:  Gabriela M Stegmann; Shira Hahn; Julie Liss; Jeremy Shefner; Seward B Rutkove; Kan Kawabata; Samarth Bhandari; Kerisa Shelton; Cayla Jessica Duncan; Visar Berisha
Journal:  Digit Biomark       Date:  2020-12-02

2.  Voice Analysis for Neurological Disorder Recognition-A Systematic Review and Perspective on Emerging Trends.

Authors:  Pascal Hecker; Nico Steckhan; Florian Eyben; Björn W Schuller; Bert Arnrich
Journal:  Front Digit Health       Date:  2022-07-07

3.  Early detection and tracking of bulbar changes in ALS via frequent and remote speech analysis.

Authors:  Gabriela M Stegmann; Shira Hahn; Julie Liss; Jeremy Shefner; Seward Rutkove; Kerisa Shelton; Cayla Jessica Duncan; Visar Berisha
Journal:  NPJ Digit Med       Date:  2020-10-13
  3 in total

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