Literature DB >> 33373483

Guidelines for Speech Recording and Acoustic Analyses in Dysarthrias of Movement Disorders.

Jan Rusz1,2, Tereza Tykalova1, Lorraine O Ramig3,4,5,6, Elina Tripoliti7.   

Abstract

Most patients with movement disorders have speech impairments resulting from sensorimotor abnormalities that affect phonatory, articulatory, and prosodic speech subsystems. There is widespread cross-discipline use of speech recordings for diagnostic and research purposes, despite which there are no specific guidelines for a standardized method. This review aims to combine the specific clinical presentations of patients with movement disorders, existing acoustic assessment protocols, and technological advances in capturing speech to provide a basis for future research in this field and to improve the consistency of clinical assessments. We considered 3 areas: the recording environment (room, seating, background noise), the recording process (instrumentation, vocal tasks, elicitation of speech samples), and the acoustic outcome data. Four vocal tasks, namely, sustained vowel, sequential and alternating motion rates, reading passage, and monologues, are integral aspects of motor speech assessment. Fourteen acoustic vocal speech features, including their hypothesized pathomechanisms with regard to typical occurrences in hypokinetic or hyperkinetic dysarthria, are hereby recommended for quantitative exploratory analysis. Using these acoustic features and experimental speech data, we demonstrated that the hyperkinetic dysarthria group had more affected speech dimensions compared with the healthy controls than had the hypokinetic speakers. Several contrasting speech patterns between both dysarthrias were also found. This article is the first attempt to provide initial recommendations for a standardized way of recording the voice and speech of patients with hypokinetic or hyperkinetic dysarthria; thus allowing clinicians and researchers to reliably collect, acoustically analyze, and compare vocal data across different centers and patient cohorts.
© 2020 International Parkinson and Movement Disorder Society. © 2020 International Parkinson and Movement Disorder Society.

Entities:  

Keywords:  Parkinson's disease; acoustic analyses; basal ganglia; dysarthria; speech and voice disorder

Mesh:

Year:  2020        PMID: 33373483     DOI: 10.1002/mds.28465

Source DB:  PubMed          Journal:  Mov Disord        ISSN: 0885-3185            Impact factor:   10.338


  8 in total

1.  Articulatory undershoot of vowels in isolated REM sleep behavior disorder and early Parkinson's disease.

Authors:  Dominik Skrabal; Jan Rusz; Michal Novotny; Karel Sonka; Evzen Ruzicka; Petr Dusek; Tereza Tykalova
Journal:  NPJ Parkinsons Dis       Date:  2022-10-20

2.  Parkinson's disease patients with freezing of gait have more severe voice impairment than non-freezers during "ON state".

Authors:  Qian Yu; Xiaoya Zou; Fengying Quan; Zhaoying Dong; Huimei Yin; Jinjing Liu; Hongzhou Zuo; Jiaman Xu; Yu Han; Dezhi Zou; Yongming Li; Oumei Cheng
Journal:  J Neural Transm (Vienna)       Date:  2022-01-06       Impact factor: 3.850

3.  Speech Biomarkers in Rapid Eye Movement Sleep Behavior Disorder and Parkinson Disease.

Authors:  Jan Rusz; Jan Hlavnička; Michal Novotný; Tereza Tykalová; Amelie Pelletier; Jacques Montplaisir; Jean-Francois Gagnon; Petr Dušek; Andrea Galbiati; Sara Marelli; Paul C Timm; Luke N Teigen; Annette Janzen; Mahboubeh Habibi; Ambra Stefani; Evi Holzknecht; Klaus Seppi; Elisa Evangelista; Anna Laura Rassu; Yves Dauvilliers; Birgit Högl; Wolfgang Oertel; Erik K St Louis; Luigi Ferini-Strambi; Evžen Růžička; Ronald B Postuma; Karel Šonka
Journal:  Ann Neurol       Date:  2021-05-07       Impact factor: 10.422

4.  Assessment of Acoustic Features and Machine Learning for Parkinson's Detection.

Authors:  Moumita Pramanik; Ratika Pradhan; Parvati Nandy; Saeed Mian Qaisar; Akash Kumar Bhoi
Journal:  J Healthc Eng       Date:  2021-08-21       Impact factor: 2.682

5.  Voice in Parkinson's Disease: A Machine Learning Study.

Authors:  Antonio Suppa; Giovanni Costantini; Francesco Asci; Pietro Di Leo; Mohammad Sami Al-Wardat; Giulia Di Lazzaro; Simona Scalise; Antonio Pisani; Giovanni Saggio
Journal:  Front Neurol       Date:  2022-02-15       Impact factor: 4.003

6.  Study protocol for using a smartphone application to investigate speech biomarkers of Parkinson's disease and other synucleinopathies: SMARTSPEECH.

Authors:  Tomáš Kouba; Vojtěch Illner; Jan Rusz
Journal:  BMJ Open       Date:  2022-06-30       Impact factor: 3.006

7.  Evaluating a Speech-Specific and a Computerized Step-Training-Specific Rhythmic Intervention in Parkinson's Disease: A Cross-Over, Multi-Arms Parallel Study.

Authors:  Anne Dorothée Rösch; Ethan Taub; Ute Gschwandtner; Peter Fuhr
Journal:  Front Rehabil Sci       Date:  2022-01-14

8.  Transcranial direct current stimulation over the primary motor cortex improves speech production in post-stroke dysarthric speakers: A randomized pilot study.

Authors:  Min Ney Wong; Faisal Nouman Baig; Yeuk Ki Chan; Manwa L Ng; Frank F Zhu; Joseph Shiu Kwong Kwan
Journal:  PLoS One       Date:  2022-10-13       Impact factor: 3.752

  8 in total

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