Glottal Source Analysis of Voice Deficits in Newly Diagnosed Drug-naïve Patients with Parkinson’s Disease: Correlation Between Acoustic Speech Characteristics and Non-Speech Motor Performance

A bibliometric analysis of speech and language impairments in Parkinson's disease based on Web of Science

Many individuals with Parkinson's disease suffer from speech and language impairments that significantly impact their quality of life. Despite several studies on these disorders, there is a lack of relevant bibliometric analyses. This paper conducted a bibliometric analysis of 3,610 papers on speech and language impairments in Parkinson's disease patients from January 1961 to November 2023, based on the Web of Science Core Collection database. Using Citespace software, the analysis focused on annual publication volume, cooperation among countries and institutions, author collaborations, journals, co-citation references, and keywords, aiming to explore the current research status, hotspots, and frontiers in this field. The number of annual publications related to speech and language impairment in Parkinson's disease have been increasing over the years. The USA leads in the number of publications. Research hotspots include the mechanism underlying speech and language impairments, clinical symptoms, automated diagnosis and classification of patients with PD using linguistic makers, and rehabilitation interventions.

Validation of cepstral peak prominence in assessing early voice changes of Parkinson's disease: Effect of speaking task and ambient noise

Although the cepstral peak prominence (CPP) and its variant, the cepstral peak prominence smooth (CPPS), are considered to be robust acoustic measures for the evaluation of dysphonia, whether they are sensitive to capture early voice changes in Parkinson's disease (PD) has not yet been explored. This study aimed to investigate the voice changes via the CPP measures in the idiopathic rapid eye movement sleep behavior disorder (iRBD), a special case of prodromal neurodegeneration, and recently diagnosed and advanced-stage Parkinson's disease (AS-PD) patients using different speaking tasks across noise-free and noisy environments. The sustained vowel phonation, reading of passages, and monologues of 60 early stage untreated PD, 30 advanced-stage Parkinson's disease, 60 iRBD, and 60 healthy control (HC) participants were evaluated. Significant differences were found between the PD groups and controls in sustained phonation via the CPP (p < 0.05) and CPPS (p < 0.01) and the monologue via the CPP (p < 0.01), although neither the CPP nor CPPS measures were sufficiently sensitive to capture the possible prodromal dysphonia in the iRBD. The quality of the CPP and CPPS measures was influenced substantially by the addition of ambient noise. It was anticipated that the CPP measures might serve as a promising digital biomarker in assessing the dysphonia from the early stages of PD.

Defining Speech Subtypes in De Novo Parkinson Disease: Response to Long-term Levodopa Therapy

BACKGROUND AND OBJECTIVES

Patterns of speech disorder in Parkinson disease (PD), which are highly variable across individual patients, have not been systematically studied. Our aim was to identify speech subtypes in treatment-naive patients with PD and to examine their response to long-term dopaminergic therapy.

METHODS

We recorded speech data from a total of 111 participants with de novo PD; 83 of the participants completed the 12-month follow-up (69 patients with PD on stable dopaminergic medication and 14 untreated controls with PD). Unsupervised k-means cluster analysis was performed on 8 distinctive parameters of hypokinetic dysarthria examined with quantitative acoustic analysis.

RESULTS

Three distinct speech subtypes with similar prevalence, symptom duration, and motor severity were detected: prosodic, phonatory-prosodic, and articulatory-prosodic. Besides monopitch and monoloudness, which were common in each subtype, speech impairment was more severe in the phonatory-prosodic subtype with predominant dysphonia and the articulatory-prosodic subtype with predominant imprecise consonant articulation than in the prosodic subtype. Clinically, the prosodic subtype was characterized by a prevalence of women and younger age, while articulatory-prosodic subtype was characterized by the prevalence of men, older age, greater severity of axial gait symptoms, and poorer cognitive performance. The phonatory-prosodic subtype clinically represented intermediate status in age with mostly men and preserved cognitive performance. While speech of untreated controls with PD deteriorated over 1 year (p = 0.02), long-term dopaminergic medication maintained stable speech impairment severity in the prosodic and articulatory-prosodic subtypes and improved speech performance in patients with the phonatory-prosodic subtype (p = 0.002).

DISCUSSION

Distinct speech phenotypes in de novo PD reflect divergent underlying mechanisms and allow prediction of response of speech impairment to levodopa therapy.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that, in patients with newly diagnosed PD with speech impairment, speech phenotype is associated with levodopa responsiveness.

A mobile-assisted voice condition analysis system for Parkinson's disease: assessment of usability conditions

BACKGROUND AND OBJECTIVE

Automatic voice condition analysis systems to detect Parkinson's disease (PD) are generally based on speech data recorded under acoustically controlled conditions and professional supervision. The performance of these approaches in a free-living scenario is unknown. The aim of this research is to investigate the impact of uncontrolled conditions (realistic acoustic environment and lack of supervision) on the performance of automatic PD detection systems based on speech.

METHODS

A mobile-assisted voice condition analysis system is proposed to aid in the detection of PD using speech. The system is based on a server-client architecture. In the server, feature extraction and machine learning algorithms are designed and implemented to discriminate subjects with PD from healthy ones. The Android app allows patients to submit phonations and physicians to check the complete record of every patient. Six different machine learning classifiers are applied to compare their performance on two different speech databases. One of them is an in-house database (UEX database), collected under professional supervision by using the same Android-based smartphone in the same room, whereas the other one is an age, sex and health-status balanced subset of mPower study for PD, which provides real-world data. By applying identical methodology, single-database experiments have been performed on each database, and also cross-database tests. Cross-validation has been applied to assess generalization performance and hypothesis tests have been used to report statistically significant differences.

RESULTS

In the single-database experiments, a best accuracy rate of 0.92 (AUC = 0.98) has been obtained on UEX database, while a considerably lower best accuracy rate of 0.71 (AUC = 0.76) has been achieved using the mPower-based database. The cross-database tests provided very degraded accuracy metrics.

CONCLUSION

The results clearly show the potential of the proposed system as an aid for general practitioners to conduct triage or an additional tool for neurologists to perform diagnosis. However, due to the performance degradation observed using data from mPower study, semi-controlled conditions are encouraged, i.e., voices recorded at home by the patients themselves following a strict recording protocol and control of the information about patients by the medical doctor at charge.

Acoustic Analysis of Phonation in Children With Smith-Magenis Syndrome

Complex simultaneous neuropsychophysiological mechanisms are responsible for the processing of the information to be transmitted and for the neuromotor planning of the articulatory organs involved in speech. The nature of this set of mechanisms is closely linked to the clinical state of the subject. Thus, for example, in populations with neurodevelopmental deficits, these underlying neuropsychophysiological procedures are deficient and determine their phonation. Most of these cases with neurodevelopmental deficits are due to a genetic abnormality, as is the case in the population with Smith–Magenis syndrome (SMS). SMS is associated with neurodevelopmental deficits, intellectual disability, and a cohort of characteristic phenotypic features, including voice quality, which does not seem to be in line with the gender, age, and complexion of the diagnosed subject. The phonatory profile and speech features in this syndrome are dysphonia, high f0, excess vocal muscle stiffness, fluency alterations, numerous syllabic simplifications, phoneme omissions, and unintelligibility of speech. This exploratory study investigates whether the neuromotor deficits in children with SMS adversely affect phonation as compared to typically developing children without neuromotor deficits, which has not been previously determined. The authors compare the phonatory performance of a group of children with SMS (N = 12) with a healthy control group of children (N = 12) matched in age, gender, and grouped into two age ranges. The first group ranges from 5 to 7 years old, and the second group goes from 8 to 12 years old. Group differences were determined for two forms of acoustic analysis performed on repeated recordings of the sustained vowel /a/ F1 and F2 extraction and cepstral peak prominence (CPP). It is expected that the results will enlighten the question of the underlying neuromotor aspects of phonation in SMS population. These findings could provide evidence of the susceptibility of phonation of speech to neuromotor disturbances, regardless of their origin.

Objective vowel sound characteristics and their relationship with motor dysfunction in Asian Parkinson's disease patients

BACKGROUND

Speech impairments are very common in patients with Parkinson's disease (PD). However, knowledge of their objective characteristics and relationship to other motor symptoms amongst Asian PD patients is limited.

OBJECTIVES

To identify objective vowel sound characteristics in Thai PD patients and correlate with disease severity, as determined by UPDRS and various sub-scores.

METHOD

We evaluated 100 Thai PD patients, with a mean age of 66.56 years (±7.52) and HY of 2.7 (±1.08), and 101 age-matched controls. Phonatory evaluation, comprising of 15 objective parameters, was conducted using the Multi-Dimensional Voice Programme with a sustained /a/ phonation.

RESULTS

PD patients exhibited significantly higher values of all dimensions of the phonatory parameters evaluated compared to controls (All, p < 0.001) except for duration of sustained phonation, which was significantly shorter in PD patients. When early- and advanced-stage patients were compared, significantly different parameters were limited to frequency perturbation parameters (Jitt, p = 0.01; RAP, p = 0.013; PPQ, p = 0.01; sPPQ, p = 0.001; vF0, p = 0.011), and NHR (p = 0.028). Several significant and moderate correlations were observed between both STD and frequency perturbation parameters and UPDRS-III, bradykinesia sub-score, and gait and postural instability sub-score. Both vF0, and STD significantly correlated with UPDRS-III and sub-scores in advanced stage patients.

CONCLUSION

Our study provides objective evidence of phonatory dysfunction in Asian PD patients with certain characteristics correlated with advanced stage or different motor dysfunction. Sustained vowel phonation is a promising digital outcome for global phenotyping a large number of PD patients.

A Methodology to Differentiate Parkinson's Disease and Aging Speech Based on Glottal Flow Acoustic Analysis

Speech is controlled by axial neuromotor systems, therefore, it is highly sensitive to the effects of neurodegenerative illnesses such as Parkinson's Disease (PD). Patients suffering from PD present important alterations in speech, which are manifested in phonation, articulation, prosody, and fluency. These alterations may be evaluated using statistical methods on features obtained from glottal, spectral, cepstral, or fractal descriptions of speech. This work introduces an evaluation paradigm based on Information Theory (IT) to differentiate the effects of PD and aging on glottal amplitude distributions. The study is conducted on a database including 48 PD patients (24 males, 24 females), 48 age-matched healthy controls (HC, 24 males, 24 females), and 48 mid-age normative subjects (NS, 24 males, 24 females). It may be concluded from the study that Hierarchical Clustering (HiCl) methods produce a clear separation between the phonation of PD patients from NS subjects (accuracy of 89.6% for both male and female subsets), but the separation between PD patients and HC subjects is less efficient (accuracy of 75.0% for the male subset and 70.8% for the female subset). Conversely, using feature selection and Support Vector Machine (SVM) classification, the differentiation between PD and HC is substantially improved (accuracy of 94.8% for the male subset and 92.8% for the female subset). This improvement was mainly boosted by feature selection, at a cost of information and generalization losses. The results point to the possibility that speech deterioration may affect HC phonation with aging, reducing its difference to PD phonation.