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Dysarthria

About: Dysarthria is a research topic. Over the lifetime, 2402 publications have been published within this topic receiving 56554 citations.


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TL;DR: This article investigated the presence, degree, predictors and trajectory of dysphagia, dysphonia and dysarthria amongst adults hospitalised with COVID-19 across the Republic of Ireland (ROI) during the first wave of the pandemic.
Abstract: Objective To investigate the presence, degree, predictors and trajectory of dysphagia, dysphonia and dysarthria amongst adults hospitalised with COVID-19 across the Republic of Ireland (ROI) during the first wave of the pandemic. Study design Prospective observational cohort study METHODS: Adults with confirmed COVID-19 who were admitted into fourteen participating acute hospitals across ROI and referred to speech and language therapy between March 1st to June 30th 2020 were recruited. Outcomes obtained at initial SLT evaluation and at discharge were oral intake status (Functional Oral Intake Scale), perceptual voice quality (GRBAS), and global dysarthria rating (Dysarthria Severity Scale). Results Data from 315 adults were analysed. At initial SLT assessment, 84% required modified oral diets, and 31% required tube feeding. There were high rates of dysphonia (42%) and dysarthria (23%). History of intubation (OR 19.959, 95% CI 6.272, 63.513; p=.000), COVID-19 neurological manifestations (OR 3.592, 95% CI 1.733, 7.445; p=.001) and age (OR 1.034; 95% CI 1.002, 1.066; p=0.036) were predictive of oral intake status. History of intubation was predictive of voice quality (OR 4.250, 95% CI 1.838, 9.827; p=.001) and COVID-19 neurological manifestations were predictive of dysarthria (OR 2.275; 95% CI 1.162, 4.456; p=0.017). At discharge, there were significant improvements in oral intake (Z=-7.971; p=.000), voice quality (Z=-5.971; p=.000), and dysarthria severity (Z=-2.619; p=0.009), although need for modified oral intake (59%), dysphonia (23%) and dysarthria (14%) persisted. Conclusion Dysphagia, dysphonia and dysarthria were widespread amongst adults hospitalised with COVID-19 and they persisted for many at discharge. Prompt SLT evaluation is required to minimise complications. This article is protected by copyright. All rights reserved.

10 citations

Journal ArticleDOI
TL;DR: A detailed review of mutism following corticobulbar, striatal, and cerebellar dysfunctions is given in this article, with a detailed description of mutisms following cortical and subcortical pathology.
Abstract: Mutism can be defined as "a condition in which there is no, or very little, oral-verbal expression, whereas comprehension of speech ... is normal or at least at a considerably higher level" (Lebrun, 1990). Benson (1979) enumerates five neuroanatomical correlates of mutism: (a) damage to the Broca region, (b) lesion of the supplementary motor area of the dominant hemisphere, (c) dysfunction of the mesencephalic reticular system, (d) thalamotomy, and (e) bilateral pathology of cortical and subcortical motor structures. The last item refers to syndromes of mutism resulting from central motor disorders. Depending on location and size of the lesion this pathophysiological interpretation should hold true for the fourth point as well. In mutism due to central motor disturbances lacking verbal expression represents the most severe degree of dysarthria, i.e. anarthria. The present review provides a detailed description of mutism following corticobulbar, striatal, and cerebellar dysfunctions.

10 citations

Journal ArticleDOI
TL;DR: The present case suggests the existence of a strong functional connectivity between cerebellum and cortical regions underlying specific memory processes in a 40-year-old right-handed German-speaking man who presented with ischemic stroke in the territories of the right superior cerebellar artery and posterior inferior cerebellary artery.
Abstract: We report the case of a 40-year-old right-handed German-speaking man who presented with ischemic stroke in the territories of the right superior cerebellar artery and posterior inferior cerebellar artery. The objective of the present study was to investigate the consequences of this cerebellar damage with regard to higher cognitive functions. On admission to the stroke unit, the patient presented with dysarthria, right-sided appendicular ataxia, gait ataxia, and right-sided horizontal nystagmus (National Institutes of Health Stroke Scale, NIHSS, score 4). When examined 10 days after his stroke using a set of neuropsychological tests, he showed a marked deficit in the ability to remember when and in which context he had previously encountered verbal material. This aspect of memory, so-called 'source memory', is known to be mediated mainly by frontal and medial temporal structures. The present case suggests the existence of a strong functional connectivity between cerebellum and cortical regions underlying specific memory processes.

10 citations

Journal ArticleDOI
TL;DR: In this paper , a comparative study on the classification of dysarthria severity levels using different deep learning techniques and acoustic features is presented, where the utility of low-dimensional feature representation using subspace modeling to give i-vectors, which are then classified using DNN models.
Abstract: Assessing the severity level of dysarthria can provide an insight into the patient's improvement, assist pathologists to plan therapy, and aid automatic dysarthric speech recognition systems. In this article, we present a comparative study on the classification of dysarthria severity levels using different deep learning techniques and acoustic features. First, we evaluate the basic architectural choices such as deep neural network (DNN), convolutional neural network, gated recurrent units and long short-term memory network using the basic speech features, namely, Mel-frequency cepstral coefficients (MFCCs) and constant-Q cepstral coefficients. Next, speech-disorder specific features computed from prosody, articulation, phonation and glottal functioning are evaluated on DNN models. Finally, we explore the utility of low-dimensional feature representation using subspace modeling to give i-vectors, which are then classified using DNN models. Evaluation is done using the standard UA-Speech and TORGO databases. By giving an accuracy of 93.97% under the speaker-dependent scenario and 49.22% under the speaker-independent scenario for the UA-Speech database, the DNN classifier using MFCC-based i-vectors outperforms other systems.

10 citations

Journal ArticleDOI
TL;DR: A study is reported of patients who exhibit both dysphagia and dysarthria as a result of either stroke or Parkinson's disease, and assessments of the intelligibility of their speech and of their swallowing problems were found to be unrelated.
Abstract: Speech and language therapists are increasingly being asked to treat dysphagic patients. Concern has been expressed and surveys have confirmed that radiological assessment procedures are rarely available. Consequently, patients must often be assessed and their treatment planned on the basis of bedside examinations. Despite evidence that swallowing disorders need not be related to problems of articulation, recommendations on the procedure of such examinations frequently include an evaluation of speech and non—speech articulatory movements. A study is reported of patients who exhibit both dysphagia and dysarthria as a result of either stroke or Parkinson's disease. Assessments of the intelligibility of their speech and of their swallowing problems were found to be unrelated. The implications of this finding for the assessment of dysphagia are discussed.II est de plus en plus frequent qu'on demande aux orthophonistes de trailer des sujets souffranl de dysphagie. Ceci n'a pas manque de soulever des inquietude...

9 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023229
2022415
2021164
2020138
2019125
201888