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Computerized analysis of speech and voice for Parkinson's disease: A systematic review.
Ngo, Quoc Cuong; Motin, Mohammod Abdul; Pah, Nemuel Daniel; Drotár, Peter; Kempster, Peter; Kumar, Dinesh.
Afiliação
  • Ngo QC; Biosignals Lab, RMIT University, Melbourne, Australia.
  • Motin MA; Biosignals Lab, RMIT University, Melbourne, Australia; Department of Electrical & Electronic Engineering, Rajshahi University of Engineering & Technology, Rajshahi 6204, Bangladesh.
  • Pah ND; Biosignals Lab, RMIT University, Melbourne, Australia; Universitas Surabaya, Indonesia.
  • Drotár P; Intelligent Information Systems Lab, Technical University of Kosice, Letna 9, 42001, Kosice, Slovakia.
  • Kempster P; Neurosciences Department, Monash Health, Clayton, VIC, Australia; Department of Medicine, School of Clinical Sciences, Monash University, Clayton, VIC, Australia.
  • Kumar D; Biosignals Lab, RMIT University, Melbourne, Australia. Electronic address: dinesh.kumar@rmit.edu.au.
Comput Methods Programs Biomed ; 226: 107133, 2022 Nov.
Article em En | MEDLINE | ID: mdl-36183641
ABSTRACT
BACKGROUND AND

OBJECTIVE:

Speech impairment is an early symptom of Parkinson's disease (PD). This study has summarized the literature related to speech and voice in detecting PD and assessing its severity.

METHODS:

A systematic review of the literature from 2010 to 2021 to investigate analysis methods and signal features. The keywords "Automatic analysis" in conjunction with "PD speech" or "PD voice" were used, and the PubMed and ScienceDirect databases were searched. A total of 838 papers were found on the first run, of which 189 were selected. One hundred and forty-seven were found to be suitable for the review. The different datasets, recording protocols, signal analysis methods and features that were reported are listed. Values of the features that separate PD patients from healthy controls were tabulated. Finally, the barriers that limit the wide use of computerized speech analysis are discussed.

RESULTS:

Speech and voice may be valuable markers for PD. However, large differences between the datasets make it difficult to compare different studies. In addition, speech analytic methods that are not informed by physiological understanding may alienate clinicians.

CONCLUSIONS:

The potential usefulness of speech and voice for the detection and assessment of PD is confirmed by evidence from the classification and correlation results.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Doença de Parkinson / Voz Tipo de estudo: Diagnostic_studies / Guideline / Systematic_reviews Limite: Humans Idioma: En Revista: Comput Methods Programs Biomed Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Doença de Parkinson / Voz Tipo de estudo: Diagnostic_studies / Guideline / Systematic_reviews Limite: Humans Idioma: En Revista: Comput Methods Programs Biomed Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Austrália