This multilanguage study used simple speech recording and high-end pattern analysis to provide sensitive and reliable noninvasive biomarkers of prodromal versus manifest α-synucleinopathy in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD) and early-stage Parkinson disease (PD).We performed a multicenter study across the Czech, English, German, French, and Italian languages at 7 centers in Europe and North America. A total of 448 participants (337 males), including 150 with iRBD (mean duration of iRBD across language groups 0.5-3.4 years), 149 with PD (mean duration of disease across language groups 1.7-2.5 years), and 149 healthy controls were recorded; 350 of the participants completed the 12-month follow-up. We developed a fully automated acoustic quantitative assessment approach for the 7 distinctive patterns of hypokinetic dysarthria.No differences in language that impacted clinical parkinsonian phenotypes were found. Compared with the controls, we found significant abnormalities of an overall acoustic speech severity measure via composite dysarthria index for both iRBD (p = 0.002) and PD (p < 0.001). However, only PD (p < 0.001) was perceptually distinct in a blinded subjective analysis. We found significant group differences between PD and controls for monopitch (p < 0.001), prolonged pauses (p < 0.001), and imprecise consonants (p = 0.03); only monopitch was able to differentiate iRBD patients from controls (p = 0.004). At the 12-month follow-up, a slight progression of overall acoustic speech impairment was noted for the iRBD (p = 0.04) and PD (p = 0.03) groups.Automated speech analysis might provide a useful additional biomarker of parkinsonism for the assessment of disease progression and therapeutic interventions. ANN NEUROL 2021;90:62-75.
Purpose The purpose of this research note is to provide a performance comparison of available algorithms for the automated evaluation of oral diadochokinesis using speech samples from patients with amyotrophic lateral sclerosis (ALS). Method Four different algorithms based on a wide range of signal processing approaches were tested on a sequential motion rate /pa/-/ta/-/ka/ syllable repetition paradigm collected from 18 patients with ALS and 18 age- and gender-matched healthy controls (HCs). Results The best temporal detection of syllable position for a 10-ms tolerance value was achieved for ALS patients using a traditional signal processing approach based on a combination of filtering in the spectrogram, Bayesian detection, and polynomial thresholding with an accuracy rate of 74.4%, and for HCs using a deep learning approach with an accuracy rate of 87.6%. Compared to HCs, a slow diadochokinetic rate ( p < .001) and diadochokinetic irregularity ( p < .01) were detected in ALS patients. Conclusions The approaches using deep learning or multiple-step combinations of advanced signal processing methods provided a more robust solution to the estimation of oral DDK variables than did simpler approaches based on the rough segmentation of the signal envelope. The automated acoustic assessment of oral diadochokinesis shows excellent potential for monitoring bulbar disease progression in individuals with ALS.
Background Research on the possible influence of lateralised basal ganglia dysfunction on speech in Parkinson’s disease is scarce. This study aimed to compare speech in de-novo, drug-naive patients with Parkinson’s disease (PD) with asymmetric nigral dopaminergic dysfunction, predominantly in either the right or left hemisphere. Methods Acoustic analyses of reading passages were performed. Asymmetry of nigral dysfunction was defined using dopamine transporter-single-photon emission CT (DAT-SPECT). Results From a total of 135 de novo patients with PD assessed, 47 patients had a lower right and 36 lower left DAT availability in putamen based on DAT-SPECT. Patients with PD with lower left DAT availability had higher dysarthria severity via composite dysarthria index compared with patients with lower right DAT availability (p=0.01). Conclusion Our data support the crucial role of DAT availability in the left putamen in speech. This finding might provide important clues for managing speech following deep brain stimulation.
Abstract Background The mechanisms underlying speech abnormalities in Parkinson's disease (PD) remain poorly understood, with most of the available evidence based on male patients. This study aimed to estimate the occurrence and characteristics of speech disorder in early, drug‐naive PD patients with relation to gender and dopamine transporter imaging. Methods Speech samples from 60 male and 40 female de novo PD patients as well as 60 male and 40 female age‐matched healthy controls were analyzed. Quantitative acoustic vocal assessment of 10 distinct speech dimensions related to phonation, articulation, prosody, and speech timing was performed. All patients were evaluated using [123]I‐2b‐carbomethoxy‐3b‐(4‐iodophenyl)‐N‐(3‐fluoropropyl) nortropane single‐photon emission computed tomography and Montreal Cognitive Assessment. Results The prevalence of speech abnormalities in the de novo PD cohort was 56% for male and 65% for female patients, mainly manifested with monopitch, monoloudness, and articulatory decay. Automated speech analysis enabled discrimination between PD and controls with an area under the curve of 0.86 in men and 0.93 in women. No gender‐specific speech dysfunction in de novo PD was found. Regardless of disease status, females generally showed better performance in voice quality, consonant articulation, and pauses production than males, who were better only in loudness variability. The extent of monopitch was correlated to nigro‐putaminal dopaminergic loss in men ( r = 0.39, p = 0.003) and the severity of imprecise consonants was related to cognitive deficits in women ( r = −0.44, p = 0.005). Conclusions Speech abnormalities represent a frequent and early marker of motor abnormalities in PD. Despite some gender differences, our findings demonstrate that speech difficulties are associated with nigro‐putaminal dopaminergic deficits.
