Objectives: To elucidate the phenotypes and pathophysiology of speech and voice disorders in Parkinson's disease (PD) with subthalamic nucleus deep brain stimulation (STN-DBS).
Methods: We conducted a cross-sectional study on 76 PD patients treated with bilateral STN-DBS (PD-DBS) and 33 medically treated PD patients (PD-Med). Speech and voice functions, electrode positions, motor function and cognitive function were comprehensively assessed. Moreover, speech and voice functions were compared between the on-stimulation and off-stimulation conditions in 42 PD-DBS patients.
Results: Speech and voice disorders in PD-DBS patients were significantly worse than those in PD-Med patients. Factor analysis and subsequent cluster analysis classified PD-DBS patients into five clusters: relatively good speech and voice function type, 25%; stuttering type, 24%; breathy voice type, 16%; strained voice type, 18%; and spastic dysarthria type, 17%. STN-DBS ameliorated voice tremor or low volume; however, it deteriorated the overall speech intelligibility in most patients. Breathy voice did not show significant changes and stuttering exhibited slight improvement after stopping stimulation. In contrast, patients with strained voice type or spastic dysarthria type showed a greater improvement after stopping stimulation. Spastic dysarthria type patients showed speech disorders similar to spastic dysarthria, which is associated with bilateral upper motor neuron involvement. Strained voice type and spastic dysarthria type appeared to be related to current diffusion to the corticobulbar fibres.
Conclusions: Stuttering and breathy voice can be aggravated by STN-DBS, but are mainly due to aging or PD itself. Strained voice and spastic dysarthria are considered corticobulbar side effects.
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http://dx.doi.org/10.1136/jnnp-2014-308043 | DOI Listing |
BMJ Case Rep
January 2025
Maxillofacial Surgery, Waikato Hospital, Hamilton, New Zealand.
A man in his late 50s was referred by a speech and language therapist for consideration of a palatal lift prosthesis (PLP) to improve his speech intelligibility. He presented with hypokinetic dysarthria characterised by reduced loudness, breathy voice and hypernasality. The patient had a diagnosis of progressive muscular dystrophy and mobilised in a motorised wheelchair.
View Article and Find Full Text PDFNeural Netw
January 2025
School of automotive studies, Tongji University, Shanghai 201804, China.
Integrating visual features has been proven effective for deep learning-based speech quality enhancement, particularly in highly noisy environments. However, these models may suffer from redundant information, resulting in performance deterioration when the signal-to-noise ratio (SNR) is relatively high. Real-world noisy scenarios typically exhibit widely varying noise levels.
View Article and Find Full Text PDFJ Voice
January 2025
Universidade Estadual de Campinas - UNICAMP, Campinas, São Paulo, Brazil. Electronic address:
Objective: To analyze acoustic measures of speech and vowel samples from individuals of different genders and to correlate these acoustic measures with vocal satisfaction. This study aims to provide additional data on acoustic measures, serving as references for clinicians while emphasizing the importance of moving beyond cisgender norms. Additionally, it addresses a gap in the Brazilian context by exploring correlations between acoustic measures and self-perceived vocal satisfaction across diverse gender groups.
View Article and Find Full Text PDFClin Linguist Phon
January 2025
École d'orthophonie et d'audiologie, Faculté de médecine, Université de Montréal, Québec, Canada.
This article presents the Quebec French adaptation of the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V), a standardised protocol for evaluating voice quality. Developed through collaboration within the Quebec Voice Speech-Language Pathologist (SLP) Community of Practice, the adapted tool addresses linguistic and cultural nuances specific to Quebec French. This adaptation ensures standardised assessments and harmonises clinical and research practices across the province.
View Article and Find Full Text PDFInt J Chron Obstruct Pulmon Dis
January 2025
Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany.
Background: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Methods: In this single centre study, non-consecutive COPD patients were prospectively recruited for comparing their speech characteristics during and after an acute COPD exacerbation.
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