Speech abnormalities in Parkinson's disease (PD) are heterogeneous and often considered resistant to levodopa. However, human hearing may miss subtle treatment-related speech changes. Digital speech biomarkers offer a sensitive alternative to measure such changes objectively. Speech was recorded in 51 PD patients during ON and OFF medication states and compared to 43 healthy controls matched for language and gender. Acute levodopa effects were significant in prosodic (F0 standard deviation, p = 0.03, effect size = 0.47), respiratory (intensity slope, p = 0.02, effect size = 0.49), and spectral domains (LTAS mean, p = 0.01, effect size = 0.35). Stepwise backward regression identified 8 biomarkers reflecting hypokinetic symptoms, 6 for dyskinetic symptoms, and 7 for medication-state transitions. Hypokinetic compound score correlated strongly with MDS-UPDRS-III changes (r = 0.70; MAE = 6.06/92), and the dyskinetic compound score with dyskinesia ratings (r = 0.50; MAE = 1.81/12). Medication-state transitions were detected with AUC = 0.86. This study highlights the potential of digital speech biomarkers to objectively measure levodopa-induced changes in PD symptoms and medication states.

• Publikační typ
• časopisecké články MeSH

BACKGROUND AND OBJECTIVES: The impact of dopaminergic medication on language in Parkinson's disease (PD) remains poorly understood. This observational, naturalistic study aimed to investigate the effects of long-term dopaminergic therapy on language performance in patients with de-novo PD based on a high-level linguistic analysis of natural spontaneous discourse. METHODS: A fairy-tale narration was recorded at baseline and a 12-month follow-up. The speech samples were automatically analyzed using six representative lexical and syntactic features based on automatic speech recognition and natural language processing. RESULTS: We enrolled 109 de-novo PD patients compared to 68 healthy controls. All subjects completed the 12-month follow-up; 92 PD patients were on stable dopaminergic medication (PD-treated), while 17 PD patients remained without medication (PD-untreated). At baseline, the PD-treated group exhibited abnormalities in syntactic domains, particularly in sentence length (p = 0.018) and sentence development (p = 0.042) compared to healthy controls. After 12 months of dopaminergic therapy, PD-treated showed improvements in the syntactic domain, including sentence length (p = 0.012) and sentence development (p = 0.030). Of all PD-treated patients, 37 were on monotherapy with dopamine agonists and manifested improvement in sentence length (p = 0.048), while 32 were on monotherapy with levodopa and had no language amelioration. No changes in language parameters over time were seen in both the PD-untreated group and healthy controls. DISCUSSION: Initiation of dopaminergic therapy improved high-language syntactic deficits in de-novo PD, confirming the role of dopamine in cognitive-linguistic processing. Automated linguistic analysis of spontaneous speech via natural language processing can assist in improving the prediction and management of language deficits in PD.

• Klíčová slova
• Discourse, Levodopa, Linguistic analysis, Natural language processing, Speech,
• MeSH
• agonisté dopaminu * terapeutické užití   MeSH
• antiparkinsonika * terapeutické užití   MeSH
• dopaminové látky * terapeutické užití   MeSH
• lidé středního věku MeSH
• lidé MeSH
• následné studie MeSH
• Parkinsonova nemoc * farmakoterapie   komplikace   MeSH
• řeč * účinky léků   MeSH
• senioři MeSH
• výsledek terapie MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• pozorovací studie MeSH
• Názvy látek
• agonisté dopaminu * MeSH
• antiparkinsonika * MeSH
• dopaminové látky * MeSH

BACKGROUND AND OBJECTIVES: Patients with synucleinopathies such as multiple system atrophy (MSA) and Parkinson's disease (PD) frequently display speech and language abnormalities. We explore the diagnostic potential of automated linguistic analysis of natural spontaneous speech to differentiate MSA and PD. METHODS: Spontaneous speech of 39 participants with MSA compared to 39 drug-naive PD and 39 healthy controls matched for age and sex was transcribed and linguistically annotated using automatic speech recognition and natural language processing. A quantitative analysis was performed using 6 lexical and syntactic and 2 acoustic features. Results were compared with human-controlled analysis to assess the robustness of the approach. Diagnostic accuracy was evaluated using sensitivity analysis. RESULTS: Despite similar disease duration, linguistic abnormalities were generally more severe in MSA than in PD, leading to high diagnostic accuracy with an area under the curve of 0.81. Compared to controls, MSA showed decreased grammatical component usage, more repetitive phrases, shorter sentences, reduced sentence development, slower articulation rate, and increased duration of pauses, whereas PD had only shorter sentences, reduced sentence development, and longer pauses. Only slower articulation rate was distinctive for MSA while unchanged for PD relative to controls. The highest correlation was found between bulbar/pseudobulbar clinical score and sentence length (r = -0.49, p = 0.002). Despite the relatively high severity of dysarthria in MSA, a strong agreement between manually and automatically computed results was achieved. DISCUSSION: Automated linguistic analysis may offer an objective, cost-effective, and widely applicable biomarker to differentiate synucleinopathies with similar clinical manifestations.

• Klíčová slova
• Automated linguistic analysis, Language, Multiple system atrophy, Natural language processing, Spontaneous discourse,
• MeSH
• diferenciální diagnóza MeSH
• lidé středního věku MeSH
• lidé MeSH
• multisystémová atrofie * diagnóza   komplikace   MeSH
• Parkinsonova nemoc * diagnóza   komplikace   MeSH
• senioři MeSH
• zpracování přirozeného jazyka * MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH

INTRODUCTION: Hypokinetic dysarthria (HD) is a common motor speech symptom of Parkinson's disease (PD) which does not respond well to PD treatments. We investigated short-term effects of transcranial direct current stimulation (tDCS) on HD in PD using acoustic analysis of speech. Based on our previous studies we focused on stimulation of the right superior temporal gyrus (STG) - an auditory feedback area. METHODS: In 14 PD patients with HD, we applied anodal, cathodal and sham tDCS to the right STG using a cross-over design. A protocol consisting of speech tasks was performed prior to and immediately after each stimulation session. Linear mixed models were used for the evaluation of the effects of each stimulation condition on the relative change of acoustic parameters. We also performed a simulation of the mean electric field induced by tDCS. RESULTS: Linear mixed model showed a statistically significant effect of the stimulation condition on the relative change of median duration of silences longer than 50 ms (p = 0.015). The relative change after the anodal stimulation (mean = -5.9) was significantly lower as compared to the relative change after the sham stimulation (mean = 12.8), p = 0.014. We also found a correlation between the mean electric field magnitude in the right STG and improvement of articulation precision after anodal tDCS (R = 0.637; p = 0.019). CONCLUSIONS: The exploratory study showed that anodal tDCS applied over the auditory feedback area may lead to shorter pauses in a speech of PD patients.

• Klíčová slova
• Acoustic analysis, Hypokinetic dysarthria, Parkinson’s disease, Superior temporal gyrus, Transcranial electric stimulation,
• MeSH
• dysartrie etiologie   terapie   patofyziologie   MeSH
• klinické křížové studie MeSH
• lidé středního věku MeSH
• lidé MeSH
• Parkinsonova nemoc * terapie   komplikace   patofyziologie   MeSH
• pilotní projekty MeSH
• přímá transkraniální stimulace mozku * MeSH
• řeč fyziologie   MeSH
• senioři MeSH
• spánkový lalok patofyziologie   MeSH
• výsledek terapie MeSH
• Check Tag
• lidé středního věku MeSH
• lidé MeSH
• mužské pohlaví MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Approximately 90% of Parkinson's patients (PD) suffer from dysarthria. However, there is currently a lack of research on acoustic measurements and speech impairment patterns among Mandarin-speaking individuals with PD. This study aims to assess the diagnosis and disease monitoring possibility in Mandarin-speaking PD patients through the recommended speech paradigm for non-tonal languages, and to explore the anatomical and functional substrates. We examined total of 160 native Mandarin-speaking Chinese participants consisting of 80 PD patients, 40 healthy controls (HC), and 40 MRI controls. We screened the optimal acoustic metric combination for PD diagnosis. Finally, we used the objective metrics to predict the patient's motor status using the Naïve Bayes model and analyzed the correlations between cortical thickness, subcortical volumes, functional connectivity, and network properties. Comprehensive acoustic screening based on prosodic, articulation, and phonation abnormalities allows differentiation between HC and PD with an area under the curve of 0.931. Patients with slowed reading exhibited atrophy of the fusiform gyrus (FDR p = 0.010, R = 0.391), reduced functional connectivity between the fusiform gyrus and motor cortex, and increased nodal local efficiency (NLE) and nodal efficiency (NE) in bilateral pallidum. Patients with prolonged pauses demonstrated atrophy in the left hippocampus, along with decreased NLE and NE. The acoustic assessment in Mandarin proves effective in diagnosis and disease monitoring for Mandarin-speaking PD patients, generalizing standardized acoustic guidelines beyond non-tonal languages. The speech impairment in Mandarin-speaking PD patients not only involves motor aspects of speech but also encompasses the cognitive processes underlying language generation.

• Publikační typ
• časopisecké články MeSH
• přehledy MeSH

Parkinson's disease (PD) and essential tremor (ET) are prevalent movement disorders that mainly affect elderly people, presenting diagnostic challenges due to shared clinical features. While both disorders exhibit distinct speech patterns-hypokinetic dysarthria in PD and hyperkinetic dysarthria in ET-the efficacy of speech assessment for differentiation remains unexplored. Developing technology for automatic discrimination could enable early diagnosis and continuous monitoring. However, the lack of data for investigating speech behavior in these patients has inhibited the development of a framework for diagnostic support. In addition, phonetic variability across languages poses practical challenges in establishing a universal speech assessment system. Therefore, it is necessary to develop models robust to the phonetic variability present in different languages worldwide. We propose a method based on Gaussian mixture models to assess domain adaptation from models trained in German and Spanish to classify PD and ET patients in Czech. We modeled three different speech dimensions: articulation, phonation, and prosody and evaluated the models' performance in both bi-class and tri-class classification scenarios (with the addition of healthy controls). Our results show that a fusion of the three speech dimensions achieved optimal results in binary classification, with accuracies up to 81.4 and 86.2% for monologue and /pa-ta-ka/ tasks, respectively. In tri-class scenarios, incorporating healthy speech signals resulted in accuracies of 63.3 and 71.6% for monologue and /pa-ta-ka/ tasks, respectively. Our findings suggest that automated speech analysis, combined with machine learning is robust, accurate, and can be adapted to different languages to distinguish between PD and ET patients.

• Publikační typ
• časopisecké články MeSH

Hypokinetic dysarthria (HD) is a difficult-to-treat symptom affecting quality of life in patients with Parkinson's disease (PD). Levodopa may partially alleviate some symptoms of HD in PD, but the neural correlates of these effects are not fully understood. The aim of our study was to identify neural mechanisms by which levodopa affects articulation and prosody in patients with PD. Altogether 20 PD patients participated in a task fMRI study (overt sentence reading). Using a single dose of levodopa after an overnight withdrawal of dopaminergic medication, levodopa-induced BOLD signal changes within the articulatory pathway (in regions of interest; ROIs) were studied. We also correlated levodopa-induced BOLD signal changes with the changes in acoustic parameters of speech. We observed no significant changes in acoustic parameters due to acute levodopa administration. After levodopa administration as compared to the OFF dopaminergic condition, patients showed task-induced BOLD signal decreases in the left ventral thalamus (p = 0.0033). The changes in thalamic activation were associated with changes in pitch variation (R = 0.67, p = 0.006), while the changes in caudate nucleus activation were related to changes in the second formant variability which evaluates precise articulation (R = 0.70, p = 0.003). The results are in line with the notion that levodopa does not have a major impact on HD in PD, but it may induce neural changes within the basal ganglia circuitries that are related to changes in speech prosody and articulation.

• Klíčová slova
• Hypokinetic dysarthria, Levodopa, Parkinson’s disease, Task fMRI,
• MeSH
• antiparkinsonika škodlivé účinky   MeSH
• dysartrie etiologie   komplikace   MeSH
• kvalita života MeSH
• levodopa * škodlivé účinky   MeSH
• lidé MeSH
• magnetická rezonanční tomografie metody   MeSH
• Parkinsonova nemoc * komplikace   diagnostické zobrazování   farmakoterapie   MeSH
• poruchy řeči diagnostické zobrazování   etiologie   MeSH
• řeč fyziologie   MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• antiparkinsonika MeSH
• levodopa * MeSH

AIM: To investigate the presence and relationship of temporal speech and gait parameters in patients with postural instability/gait disorder (PIGD) and tremor-dominant (TD) motor subtypes of Parkinson's disease (PD). METHODS: Speech samples and instrumented walkway system assessments were acquired from a total of 60 de-novo PD patients (40 in TD and 20 in PIGD subtype) and 40 matched healthy controls. Objective acoustic vocal assessment of seven distinct speech timing dimensions was related to instrumental gait measures including velocity, cadence, and stride length. RESULTS: Compared to controls, PIGD subtype showed greater consonant timing abnormalities by prolonged voice onset time (VOT) while also shorter stride length during both normal walking and dual task, while decreased velocity and cadence only during dual task. Speaking rate was faster in PIGD than TD subtype. In PIGD subtype, prolonged VOT correlated with slower gait velocity (r = -0.56, p = 0.01) and shorter stride length (r = -0.59, p = 0.008) during normal walking, whereas relationships were also found between decreased cadence in dual task and irregular alternating motion rates (r = -0.48, p = 0.04) and prolonged pauses (r = -0.50, p = 0.03). No correlation between speech and gait was detected in TD subtype. CONCLUSION: Our findings suggest that speech and gait rhythm disorder share similar underlying pathomechanisms specific for PIGD subtype.

• Klíčová slova
• Parkinson's disease, dysarthria, gait, postural instability gait difficulty, speech disorder,
• MeSH
• chůze (způsob) MeSH
• chůze MeSH
• lidé MeSH
• neurologické poruchy chůze * etiologie   MeSH
• Parkinsonova nemoc * komplikace   MeSH
• posturální rovnováha MeSH
• řeč MeSH
• tremor MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

While speech disorder represents an early and prominent clinical feature of atypical parkinsonian syndromes such as multiple system atrophy (MSA) and progressive supranuclear palsy (PSP), little is known about the sensitivity of speech assessment as a potential diagnostic tool. Speech samples were acquired from 215 subjects, including 25 MSA, 20 PSP, 20 Parkinson's disease participants, and 150 healthy controls. The accurate differential diagnosis of dysarthria subtypes was based on the quantitative acoustic analysis of 26 speech dimensions related to phonation, articulation, prosody, and timing. A semi-supervised weighting-based approach was then applied to find the best feature combinations for separation between PSP and MSA. Dysarthria was perceptible in all PSP and MSA patients and consisted of a combination of hypokinetic, spastic, and ataxic components. Speech features related to respiratory dysfunction, imprecise consonants, monopitch, slow speaking rate, and subharmonics contributed to worse performance in PSP than MSA, whereas phonatory instability, timing abnormalities, and articulatory decay were more distinctive for MSA compared to PSP. The combination of distinct speech patterns via objective acoustic evaluation was able to discriminate between PSP and MSA with very high accuracy of up to 89% as well as between PSP/MSA and PD with up to 87%. Dysarthria severity in MSA/PSP was related to overall disease severity. Speech disorders reflect the differing underlying pathophysiology of tauopathy in PSP and α-synucleinopathy in MSA. Vocal assessment may provide a low-cost alternative screening method to existing subjective clinical assessment and imaging diagnostic approaches.

• Publikační typ
• časopisecké články MeSH

Imprecise vowels represent a common deficit associated with hypokinetic dysarthria resulting from a reduced articulatory range of motion in Parkinson's disease (PD). It is not yet unknown whether the vowel articulation impairment is already evident in the prodromal stages of synucleinopathy. We aimed to assess whether vowel articulation abnormalities are present in isolated rapid eye movement sleep behaviour disorder (iRBD) and early-stage PD. A total of 180 male participants, including 60 iRBD, 60 de-novo PD and 60 age-matched healthy controls performed reading of a standardized passage. The first and second formant frequencies of the corner vowels /a/, /i/, and /u/ extracted from predefined words, were utilized to construct articulatory-acoustic measures of Vowel Space Area (VSA) and Vowel Articulation Index (VAI). Compared to controls, VSA was smaller in both iRBD (p = 0.01) and PD (p = 0.001) while VAI was lower only in PD (p = 0.002). iRBD subgroup with abnormal olfactory function had smaller VSA compared to iRBD subgroup with preserved olfactory function (p = 0.02). In PD patients, the extent of bradykinesia and rigidity correlated with VSA (r = -0.33, p = 0.01), while no correlation between axial gait symptoms or tremor and vowel articulation was detected. Vowel articulation impairment represents an early prodromal symptom in the disease process of synucleinopathy. Acoustic assessment of vowel articulation may provide a surrogate marker of synucleinopathy in scenarios where a single robust feature to monitor the dysarthria progression is needed.

• Publikační typ
• časopisecké články MeSH