Comparative analysis of speech impairment and upper limb motor dysfunction in Parkinson’s disease

A Systematic Review and Bayesian Meta-Analysis of Acoustic Measures of Prosody in Parkinson's Disease

PURPOSE

Linguistic prosody is affected in Parkinson's disease (PD), which implicates the basal ganglia's role in the production of prosody. However, there is no recent systematic synthesis of the available acoustic evidence of prosodic impairment in PD. This study aimed to identify the acoustic features of linguistic prosody that are consistently affected in PD.

METHOD

The authors systematically reviewed articles that reported acoustic features of prosodic production in PD. Articles focused on fundamental frequency (F0) and its variability, intensity and its variability, speech and articulation rate, and pause duration and ratio. From a total of 648 records identified, 36 met criteria for inclusion and exclusion. For each acoustic measurement and task, data from people with PD (PwPD) were compared with those from controls to extract effect sizes. Pooled effect sizes were estimated using robust Bayesian hierarchical regression models.

RESULTS

PD was associated with decreased F0 variability and increased pause duration. There was limited evidence of reduced intensity variability and speech rate in PwPD. No evidence was found to suggest that PD affects articulation rate or pause ratio.

CONCLUSIONS

The primary acoustic parameters of prosody affected by PD are F0 variability and pause duration. The identification of these acoustic parameters has important clinical implications for the selection of PD management strategies. The association of F0 variability and pause duration with PD suggests that the neural circuits controlling these parameters are at least partly shared and might include the basal ganglia. While the current study focused on the phonetic realization of prosodic cues, future studies should examine whether and how PD affects prosody at higher levels of processing.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.25892923.

Theta oscillations within right dorsolateral prefrontal cortex contribute differently to speech versus limb inhibition

Evidence suggests that speech and limb movement inhibition are subserved by common neural mechanisms, particularly within the right prefrontal cortex. In a recent study, we found that cathodal stimulation of right dorsolateral prefrontal cortex (rDLPFC) differentially modulated P3 event-related potentials for speech versus limb inhibition. In the present study, we further analyzed these data to examine the effects of cathodal high-definition transcranial direct current stimulation (HD-tDCS) over rDLPFC on frontal theta - an oscillatory marker of cognitive control - in response to speech and limb inhibition, during a Go/No-Go task in 21 neurotypical adults. Electroencephalography data demonstrated that both speech and limb No-Go elicited prominent theta activity over right prefrontal electrodes, with stronger activity for speech compared to limb. Moreover, we found that cathodal stimulation significantly increased theta power over right prefrontal electrodes for speech versus limb No-Go. Source analysis revealed that cathodal, but not sham, stimulation increased theta activity within rDLPFC and bilateral premotor cortex for speech No-Go compared to limb movement inhibition. These findings complement our previous report and suggest (1) right prefrontal theta activity is an amodal oscillatory mechanism supporting speech and limb inhibition, (2) larger theta activity in prefrontal electrodes for speech versus limb following cathodal stimulation may reflect allocation of additional neural resources for a more complex motor task, such as speech compared to limb movement. These findings have translational implications for conditions such as Parkinson's disease, wherein both speech and limb movement are impaired.

Cervical proprioception in Parkinson's disease and its correlation with manual dexterity function

OBJECTIVE

Cervical proprioception plays a crucial role in posture and movement control. This study aimed to determine the relationships of cervical proprioception, cervical muscle strength and endurance with manual dexterity and hand strength in individuals with idiopathic Parkinson's disease (PD).

METHODS

Twenty individuals with PD (mean age: 63.9 years) and 20 healthy individuals as a control group (mean age: 61.9 years) were recruited. Cervical joint position error (JPE), static endurance of neck muscles, activation of deep cervical flexor muscles (Craniocervical Flexion Test, CCFT), manual dexterity (Purdue Pegboard Test, PPT), cognitive and motor tasks of the PPT, finger tapping test (FTT), pinch strength, and grip strength were assessed.

RESULTS

Cervical JPE was significantly higher in individuals with PD than in controls (p < 0.05). The strength and endurance of the cervical muscles were significantly decreased in individuals with PD (p < 0.05). Cervical JPE measurements were negatively correlated with PPT, cognitive and motor tasks of the PPT in individuals with PD (all p < 0.05). The endurance of cervical flexor muscles was negatively correlated with PPT and cognitive PPT scores in the PD group (p < 0.05). In addition, a significant positive correlation was found between cervical flexor endurance and hand strength in the PD group (p < 0.05).

CONCLUSION

Cervical proprioception and the strength and endurance of cervical muscles decrease in individuals with PD compared to healthy individuals. Impairment of cervical proprioception appears to be associated with poorer upper extremity performance. Detailed evaluation of the cervical region in PD may help determine the factors affecting upper extremity function.

A study on the correlations between acoustic speech variables and bradykinesia in advanced Parkinson's disease

Background

Very few studies have assessed the presence of a possible correlation between speech variables and limb bradykinesia in patients with Parkinson's disease (PD). The objective of this study was to find correlations between different speech variables and upper extremity bradykinesia under different medication conditions in advanced PD patients.

Methods

Retrospective data were collected from a cohort of advanced PD patients before and after an acute levodopa challenge. Each patient was assessed with a perceptual-acoustic analysis of speech, which included several quantitative parameters [i.e., maximum phonation time (MPT) and intensity (dB)]; the Unified Parkinson's Disease Rating Scale (UPDRS) (total scores, subscores, and items); and a timed test (a tapping test for 20 s) to quantify upper extremity bradykinesia. Pearson's correlation coefficient was applied to find correlations between the different speech variables and the tapping rate.

Results

A total of 53 PD patients [men: 34; disease duration: 10.66 (SD 4.37) years; age at PD onset: 49.81 years (SD 6.12)] were included. Levodopa intake increased the MPT of sustained phonation (p < 0.01), but it reduced the speech rate (p = 0.05). In the defined-OFF condition, MPT of sustained phonation positively correlated with both bilateral mean (p = 0.044, r-value:0.299) and left (p = 0.033, r-value:0.314) tapping. In the defined-ON condition, the MPT correlated positively with bilateral mean tapping (p = 0.003), left tapping (p = 0.003), and right tapping (p = 0.008).

Conclusion

This study confirms the presence of correlations between speech acoustic variables and upper extremity bradykinesia in advanced PD patients. These findings suggest common pathophysiological mechanisms.

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.

Cognitive Determinants of Dysarthria in Parkinson's Disease: An Automated Machine Learning Approach

BACKGROUND

Dysarthric symptoms in Parkinson's disease (PD) vary greatly across cohorts. Abundant research suggests that such heterogeneity could reflect subject-level and task-related cognitive factors. However, the interplay of these variables during motor speech remains underexplored, let alone by administering validated materials to carefully matched samples with varying cognitive profiles and combining automated tools with machine learning methods.

OBJECTIVE

We aimed to identify which speech dimensions best identify patients with PD in cognitively heterogeneous, cognitively preserved, and cognitively impaired groups through tasks with low (reading) and high (retelling) processing demands.

METHODS

We used support vector machines to analyze prosodic, articulatory, and phonemic identifiability features. Patient groups were compared with healthy control subjects and against each other in both tasks, using each measure separately and in combination.

RESULTS

Relative to control subjects, patients in cognitively heterogeneous and cognitively preserved groups were best discriminated by combined dysarthric signs during reading (accuracy = 84% and 80.2%). Conversely, patients with cognitive impairment were maximally discriminated from control subjects when considering phonemic identifiability during retelling (accuracy = 86.9%). This same pattern maximally distinguished between cognitively spared and impaired patients (accuracy = 72.1%). Also, cognitive (executive) symptom severity was predicted by prosody in cognitively preserved patients and by phonemic identifiability in cognitively heterogeneous and impaired groups. No measure predicted overall motor dysfunction in any group.

CONCLUSIONS

Predominant dysarthric symptoms appear to be best captured through undemanding tasks in cognitively heterogeneous and preserved cohorts and through cognitively loaded tasks in patients with cognitive impairment. Further applications of this framework could enhance dysarthria assessments in PD. © 2021 International Parkinson and Movement Disorder Society.

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.

Speech disorders in Parkinson's disease: pathophysiology, medical management and surgical approaches

The prevalence of speech disorders among individuals with Parkinson's disease (PD) has been reported to be as high as 89%. Speech impairment in PD results from a combination of motor and nonmotor deficits. The production of speech depends upon the coordination of various motor activities: respiration, phonation, articulation, resonance and prosody. A speech disorder is defined as impairment in any of its inter-related components. Despite the high prevalence of speech disorders in PD, only 3–4% receive speech treatment. Treatment modalities include pharmacological intervention, speech therapy, surgery, deep brain stimulation and vocal fold augmentation. Although management of Parkinsonian dysarthria is clinically challenging, speech treatment in PD should be part of a multidisciplinary approach to patient care in this disease.