scholarly journals An algorithm for Parkinson’s disease speech classification based on isolated words analysis

2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Federica Amato ◽  
Luigi Borzì ◽  
Gabriella Olmo ◽  
Juan Rafael Orozco-Arroyave
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Feature Fusion ◽  
Binary Classification ◽  
Smartphone Application ◽  
Healthy Controls ◽  
Speech Impairment ◽  
Automatic Assessment ◽  
Average Value ◽  
Post Hoc

Abstract Introduction Automatic assessment of speech impairment is a cutting edge topic in Parkinson’s disease (PD). Language disorders are known to occur several years earlier than typical motor symptoms, thus speech analysis may contribute to the early diagnosis of the disease. Moreover, the remote monitoring of dysphonia could allow achieving an effective follow-up of PD clinical condition, possibly performed in the home environment. Methods In this work, we performed a multi-level analysis, progressively combining features extracted from the entire signal, the voiced segments, and the on-set/off-set regions, leading to a total number of 126 features. Furthermore, we compared the performance of early and late feature fusion schemes, aiming to identify the best model configuration and taking advantage of having 25 isolated words pronounced by each subject. We employed data from the PC-GITA database (50 healthy controls and 50 PD patients) for validation and testing. Results We implemented an optimized k-Nearest Neighbours model for the binary classification of PD patients versus healthy controls. We achieved an accuracy of 99.4% in 10-fold cross-validation and 94.3% in testing on the PC-GITA database (average value of male and female subjects). Conclusion The promising performance yielded by our model confirms the feasibility of automatic assessment of PD using voice recordings. Moreover, a post-hoc analysis of the most relevant features discloses the option of voice processing using a simple smartphone application.

scholarly journals Pupillary Response to Postural Demand in Parkinson’s Disease

2021 ◽  
Vol 9 ◽  
Author(s):  
Melike Kahya ◽  
Kelly E. Lyons ◽  
Rajesh Pahwa ◽  
Abiodun E. Akinwuntan ◽  
Jianghua He ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Postural Control ◽  
Dual Task ◽  
Pupillary Response ◽  
Cognitive Workload ◽  
Healthy Controls ◽  
Balance Task ◽  
Eyes Open ◽  
Post Hoc

Background: Individuals with Parkinson’s disease (PD) may need to spend more mental and physical effort (i.e., cognitive workload) to maintain postural control. Pupillary response reflects cognitive workload during postural control tasks in healthy controls but has not been investigated as a measure of postural demand in PD.Objectives: To compare pupillary response during increased postural demand using vision occlusion and dual tasking between individuals with PD and healthy controls.Methods: Thirty-three individuals with PD and thirty-five healthy controls were recruited. The four conditions lasted 60 s and involved single balance task with eyes open; single balance task with eyes occluded; dual task with eyes open; dual task with eyes occluded. The dual task comprised the Auditory Stroop test. Pupillary response was recorded using an eye tracker. The balance was assessed by using a force plate. Two-way Repeated Measures ANOVA and LSD post-hoc tests were employed to compare pupillary response and Center of Pressure (CoP) displacement across the four conditions and between individuals with PD and healthy controls.Results: Pupillary response was higher in individuals with PD compared to healthy controls (p = 0.009) and increased with more challenging postural conditions in both groups (p < 0.001). The post-hoc analysis demonstrated increased pupillary response in the single balance eyes occluded (p < 0.001), dual task eyes open (p = 0.01), and dual task eyes occluded (p < 0.001) conditions compared to single task eyes open condition.Conclusion: Overall, the PD group had increased pupillary response with increased postural demand compared to the healthy controls. In the future, pupillary response can be a potential tool to understand the neurophysiological underpinnings of falls risk in the PD population.

scholarly journals Global efficiency of the motor network is decreased in Parkinson's disease in comparison with essential tremor and healthy controls

2021 ◽  
Author(s):  
Natalia Pelizari Novaes ◽  
Joana Bisol Balardin ◽  
Fabiana Campos Hirata ◽  
Luciano Melo ◽  
Edson Amaro ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Essential Tremor ◽  
Healthy Controls ◽  
Global Efficiency ◽  
Motor Network

Vestibular semicircular canal function as detected by video Head Impulse Test (vHIT) is essentially unchanged in people with Parkinson’s disease compared to healthy controls

2021 ◽  
pp. 1-9
Author(s):  
Kim E. Hawkins ◽  
Elodie Chiarovano ◽  
Serene S. Paul ◽  
Ann M Burgess ◽  
Hamish G. MacDougall ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Semicircular Canal ◽  
Neurodegenerative Disorder ◽  
Vestibular Function ◽  
Head Impulse Test ◽  
Healthy Controls ◽  
Video Head Impulse Test ◽  
Head Impulse ◽  
Vestibulo Ocular Reflex

BACKGROUND: Parkinson’s disease (PD) is a common multi-system neurodegenerative disorder with possible vestibular system dysfunction, but prior vestibular function test findings are equivocal. OBJECTIVE: To report and compare vestibulo-ocular reflex (VOR) gain as measured by the video head impulse test (vHIT) in participants with PD, including tremor dominant and postural instability/gait dysfunction phenotypes, with healthy controls (HC). METHODS: Forty participants with PD and 40 age- and gender-matched HC had their vestibular function assessed. Lateral and vertical semicircular canal VOR gains were measured with vHIT. VOR canal gains between PD participants and HC were compared with independent samples t-tests. Two distinct PD phenotypes were compared to HC using Tukey’s ANOVA. The relationship of VOR gain with PD duration, phenotype, severity and age were investigated using logistic regression. RESULTS: There were no significant differences between groups in vHIT VOR gain for lateral or vertical canals. There was no evidence of an effect of PD severity, phenotype or age on VOR gains in the PD group. CONCLUSION: The impulsive angular VOR pathways are not significantly affected by the pathophysiological changes associated with mild to moderate PD.

scholarly journals Oral Factors That Impact the Oral Microbiota in Parkinson’s Disease

2021 ◽  
Vol 9 (8) ◽  
pp. 1616
Author(s):  
Natalia S. Rozas ◽  
Gena D. Tribble ◽  
Cameron B. Jeter
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Oral Health ◽  
Soft Tissue ◽  
Oral Hygiene ◽  
Beta Diversity ◽  
Oral Microbiota ◽  
Healthy Controls ◽  
Microbiota Composition ◽  
Salivary Ph

Patients with Parkinson’s disease (PD) are at increased risk of aspiration pneumonia, their primary cause of death. Their oral microbiota differs from healthy controls, exacerbating this risk. Our goal was to explore if poor oral health, poor oral hygiene, and dysphagia status affect the oral microbiota composition of these patients. In this cross-sectional case-control study, the oral microbiota from hard and soft tissues of patients with PD (n = 30) and age-, gender-, and education-matched healthy controls (n = 30) was compared using 16S rRNA gene sequencing for bacterial identification. Study participants completed dietary, oral hygiene, drooling, and dysphagia questionnaires, and an oral health screening. Significant differences in soft tissue beta-diversity (p < 0.005) were found, and a higher abundance of opportunistic oral pathogens was detected in patients with PD. Factors that significantly influenced soft tissue beta-diversity and microbiota composition include dysphagia, drooling (both p < 0.05), and salivary pH (p < 0.005). Thus, patients with PD show significant differences in their oral microbiota compared to the controls, which may be due, in part, to dysphagia, drooling, and salivary pH. Understanding factors that alter their oral microbiota could lead to the development of diagnostic and treatment strategies that improve the quality of life and survivability of these patients.

Development of standardized regression-based formulas to assess meaningful cognitive change in early Parkinson’s disease

2020 ◽  
Author(s):  
Hannah L Combs ◽  
Kate A Wyman-Chick ◽  
Lauren O Erickson ◽  
Michele K York
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Test Scores ◽  
Prediction Models ◽  
Early Stage ◽  
Cognitive Change ◽  
Cognitive Test ◽  
Healthy Controls ◽  
Change Over Time ◽  
Over Time

Abstract Objective Longitudinal assessment of cognitive and emotional functioning in patients with Parkinson’s disease (PD) is helpful in tracking progression of the disease, developing treatment plans, evaluating outcomes, and educating patients and families. Determining whether change over time is meaningful in neurodegenerative conditions, such as PD, can be difficult as repeat assessment of neuropsychological functioning is impacted by factors outside of cognitive change. Regression-based prediction formulas are one method by which clinicians and researchers can determine whether an observed change is meaningful. The purpose of the current study was to develop and validate regression-based prediction models of cognitive and emotional test scores for participants with early-stage idiopathic PD and healthy controls (HC) enrolled in the Parkinson’s Progression Markers Initiative (PPMI). Methods Participants with de novo PD and HC were identified retrospectively from the PPMI archival database. Data from baseline testing and 12-month follow-up were utilized in this study. In total, 688 total participants were included in the present study (NPD = 508; NHC = 185). Subjects from both groups were randomly divided into development (70%) and validation (30%) subsets. Results Early-stage idiopathic PD patients and healthy controls were similar at baseline. Regression-based models were developed for all cognitive and self-report mood measures within both populations. Within the validation subset, the predicted and observed cognitive test scores did not significantly differ, except for semantic fluency. Conclusions The prediction models can serve as useful tools for researchers and clinicians to study clinically meaningful cognitive and mood change over time in PD.

scholarly journals Prefrontal and hippocampal atrophy using 7-tesla magnetic resonance imaging in patients with Parkinson’s disease

2021 ◽  
Vol 10 (2) ◽  
pp. 205846012098809
Author(s):  
Byeong H Oh ◽  
Hyeong C Moon ◽  
Aryun Kim ◽  
Hyeon J Kim ◽  
Chae J Cheong ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Magnetic Resonance ◽  
7 Tesla ◽  
Cortical Atrophy ◽  
Automated Segmentation ◽  
Healthy Controls ◽  
Segmentation Method ◽  
Resonance Imaging

Background The pathology of Parkinson’s disease leads to morphological changes in brain structure. Currently, the progressive changes in gray matter volume that occur with time and are specific to patients with Parkinson’s disease, compared to healthy controls, remain unclear. High-tesla magnetic resonance imaging might be useful in differentiating neurological disorders by brain cortical changes. Purpose We aimed to investigate patterns in gray matter changes in patients with Parkinson’s disease by using an automated segmentation method with 7-tesla magnetic resonance imaging. Material and Methods High-resolution T1-weighted 7 tesla magnetic resonance imaging volumes of 24 hemispheres were acquired from 12 Parkinson’s disease patients and 12 age- and sex-matched healthy controls with median ages of 64.5 (range, 41–82) years and 60.5 (range, 25–74) years, respectively. Subgroup analysis was performed according to whether axial motor symptoms were present in the Parkinson’s disease patients. Cortical volume, cortical thickness, and subcortical volume were measured using a high-resolution image processing technique based on the Desikan-Killiany-Tourville atlas and an automated segmentation method (FreeSurfer version 6.0). Results After cortical reconstruction, in 7 tesla magnetic resonance imaging volume segmental analysis, compared with the healthy controls, the Parkinson’s disease patients showed global cortical atrophy, mostly in the prefrontal area (rostral middle frontal, superior frontal, inferior parietal lobule, medial orbitofrontal, rostral anterior cingulate area), and subcortical volume atrophy in limbic/paralimbic areas (fusiform, hippocampus, amygdala). Conclusion We first demonstrated that 7 tesla magnetic resonance imaging detects structural abnormalities in Parkinson’s disease patients compared to healthy controls using an automated segmentation method. Compared with the healthy controls, the Parkinson’s disease patients showed global prefrontal cortical atrophy and hippocampal area atrophy.

scholarly journals A Comparison of Pain between Parkinson’s Disease and Multiple System Atrophy: A Clinical Cross-Sectional Survey

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
He-Yang You ◽  
Lei Wu ◽  
Hai-Ting Yang ◽  
Chen Yang ◽  
Xiao-Ling Ding
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Multiple System Atrophy ◽  
Rating Scale ◽  
Depression Scale ◽  
Healthy Controls ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Disease Rating ◽  
Vas Scores

Background. Pain is frequent in Parkinson’s disease (PD) and Parkinson-plus syndrome. This study aimed to assess the prevalence, characteristics, therapy (especially the effect of dopaminergic therapy), and associated symptoms of pain in Parkinson's disease and multiple system atrophy (MSA) patients. Methods. Seventy-one PD patients, sixty-five MSA patients, and forty age-matched healthy controls were enrolled and evaluated by using the German pain questionnaire and visual analogue scale (VAS). In addition, the influence of pain in PD patients on anxiety, depression, and the quality of life was assessed with the Hospital Anxiety and Depression Scale (HADS) and Parkinson’s Disease Questionnaire (PDQ-39). Results. Compared to that of the healthy controls, the PD and MSA patients had a significantly higher presence of pain (P<0.01, P<0.01). PD patients had a higher presence of pain than MSA patients (P=0.007). No difference in VAS scores was observed between the PD and MSA patients (P=0.148). A total of 21 PD patients (42.85%) with pain and 13 MSA patients (43.33%) with pain received treatment. A total of 13 PD patients with pain and 6 MSA patients with pain had an improved pain intensity after using dopaminergic medication. The differences in the disease duration, Hoehn and Yahr stages, and scores on the Unified Parkinson’s Disease Rating Scale motor score, HAD-D, HAD-A, and PDQ-39 were significant between the PD patients with and without pain. Conclusion. PD and MSA patients are prone to pain with insufficient treatment. Pain interventions should be provided as soon as possible to improve the patient’s life.

Parkinson's disease and convergence insufficiency: a mini-review

2021 ◽  
Vol 1 (3) ◽  
pp. 108-111
Author(s):  
Mashael Al-Namaeh
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Clinical Trials ◽  
Control Group ◽  
Healthy Controls ◽  
Inclusion Criteria ◽  
Medline Search ◽  
Convergence Insufficiency ◽  
Eye Examination ◽  
The Relationship

Background: A key manifestation of Parkinson’s disease (PD) is visual impairment. Cognitive impairment has been found to overlap with convergence insufficiency (CI) in patients with PD and is associated with significantly greater near point convergence (NPC) distance. Difficulty in reading and diplopia were the most common symptoms of CI in PD. The prevalence of CI is greater among patients with PD. Therefore, this study aimed to assess the relationship between PD and CI. Methods: Studies that had included data on CI, NPC, or both were selected by searching PubMed/MEDLINE and clinicaltrails.gov, without any timeline or language limitation. The following terms were used in PubMed/MEDLINE search: ‘Clinical Trials’, ‘Parkinson’s Disease’, and ‘Convergence Insufficiency’. For clinical trials.gov database, the terms ‘Parkinson’s Disease’, ‘Convergence Insufficiency’, and ‘Completed Studies’ were used. Only those studies with control subjects were included. PubMed/MEDLINE search yielded 1,563 articles, but no article was found in the clinical trails.gov search. Twelve articles met the inclusion criteria, among which nine articles were selected as they had data on CI or NPC distance (cm), and PD.   Results: Overall, there were 1,563 articles; among them, 12 articles met the inclusion criteria. Nine articles were selected based on their data concerning CI or NPC distance (cm) and PD. Relative to the control group, the PD group had high CI. In addition, PD group showed increase in NPC distance than the control group. Conclusions: These data suggest that the patients with PD had an increased likelihood of developing CI visual symptoms, and increased NPC distance than healthy controls. These findings indicate that regular eye examination is very important for patients with PD.

scholarly journals Kinematic and Kinetic Patterns Related to Free-Walking in Parkinson’s Disease

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4224 ◽  
Author(s):  
Martín Martínez ◽  
Federico Villagra ◽  
Juan Castellote ◽  
María Pastor
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Feature Selection ◽  
Clinical Status ◽  
Automatic Classification ◽  
Healthy Controls ◽  
Double Support ◽  
Gait Asymmetry ◽  
Double Support Time ◽  
Support Time

The aim of this study is to compare the properties of free-walking at a natural pace between mild Parkinson’s disease (PD) patients during the ON-clinical status and two control groups. In-shoe pressure-sensitive insoles were used to quantify the temporal and force characteristics of a 5-min free-walking in 11 PD patients, in 16 young healthy controls, and in 12 age-matched healthy controls. Inferential statistics analyses were performed on the kinematic and kinetic parameters to compare groups’ performances, whereas feature selection analyses and automatic classification were used to identify the signature of parkinsonian gait and to assess the performance of group classification, respectively. Compared to healthy subjects, the PD patients’ gait pattern presented significant differences in kinematic parameters associated with bilateral coordination but not in kinetics. Specifically, patients showed an increased variability in double support time, greater gait asymmetry and phase deviation, and also poorer phase coordination. Feature selection analyses based on the ReliefF algorithm on the differential parameters in PD patients revealed an effect of the clinical status, especially true in double support time variability and gait asymmetry. Automatic classification of PD patients, young and senior subjects confirmed that kinematic predictors produced a slightly better classification performance than kinetic predictors. Overall, classification accuracy of groups with a linear discriminant model which included the whole set of features (i.e., demographics and parameters extracted from the sensors) was 64.1%.

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