Test-retest reliability of the unified Parkinson's disease rating scale in patients with early Parkinson's disease: results from a multicenter clinical trial

Characterizing Disease Progression in Parkinson's Disease from Videos of the Finger Tapping Test

INTRODUCTION

Parkinson's disease (PD) is characterized by motor symptoms whose progression is typically assessed using clinical scales, namely the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS). Despite its reliability, the scale is bounded by a 5-point scale that limits its ability to track subtle changes in disease progression and is prone to subjective interpretations. We aimed to develop an automated system to objectively quantify motor symptoms in PD using Machine Learning (ML) algorithms to analyze videos and capture nuanced features of disease progression.

METHODS

We analyzed videos of the Finger Tapping test, a component of the MDS-UPDRS, from 24 healthy controls and 66 PD patients using ML algorithms for hand pose estimation. We computed multiple movement features related to bradykinesia from videos and employed a novel tiered classification approach to predict disease severity that employed different features according to severity. We compared our video-based disease severity prediction approach against other approaches recently introduced in the literature.

RESULTS

Traditional kinematics features such as amplitude and velocity changed linearly with disease severity, while other non-traditional features displayed non-linear trends. The proposed disease severity prediction approach demonstrated superior accuracy in detecting PD and distinguishing between different levels of disease severity when compared to existing approaches.

Improved measurement of disease progression in people living with early Parkinson's disease using digital health technologies

BACKGROUND

Digital health technologies show promise for improving the measurement of Parkinson's disease in clinical research and trials. However, it is not clear whether digital measures demonstrate enhanced sensitivity to disease progression compared to traditional measurement approaches.

METHODS

To this end, we develop a wearable sensor-based digital algorithm for deriving features of upper and lower-body bradykinesia and evaluate the sensitivity of digital measures to 1-year longitudinal progression using data from the WATCH-PD study, a multicenter, observational digital assessment study in participants with early, untreated Parkinson's disease. In total, 82 early, untreated Parkinson's disease participants and 50 age-matched controls were recruited and took part in a variety of motor tasks over the course of a 12-month period while wearing body-worn inertial sensors. We establish clinical validity of sensor-based digital measures by investigating convergent validity with appropriate clinical constructs, known groups validity by distinguishing patients from healthy volunteers, and test-retest reliability by comparing measurements between visits.

RESULTS

We demonstrate clinical validity of the digital measures, and importantly, superior sensitivity of digital measures for distinguishing 1-year longitudinal change in early-stage PD relative to corresponding clinical constructs.

CONCLUSIONS

Our results demonstrate the potential of digital health technologies to enhance sensitivity to disease progression relative to existing measurement standards and may constitute the basis for use as drug development tools in clinical research.

Exercise-Induced Functional Changes in People with Parkinson's Disease following External Cueing and Task-Based Intervention

Introduction

The purpose of this study was to evaluate change in motor function, gait speed, dynamic balance, balance confidence, and quality of life (QoL) in nine participants with Parkinson's disease (PwPD) completing Lee Silverman Voice Treatment BIG (LSVT-BIG), an external cueing and task-based intervention. Although supported as an efficacious treatment in PwPD, there is limited research examining clinically meaningful change in outcome measures related to external cueing and task-based interventions.

Materials and Methods

This was a case series of nine PwPD (age range 64-76 years, 55% male) who completed the LSVT-BIG protocol. Disease duration ranged from 1 to 17 years and was classified as moderate in all participants (Hoehn and Yahr = 2 or 3). Outcome measures included motor function (MDS-UPDRS Part III Motor), gait speed, dynamic balance (MiniBEST), Activities-specific Balance Confidence (ABC), and Summary Index for PD Quality of Life 39 (PDQ-SI). Assessments were completed at baseline (BASE), end of treatment (EOT), and 4 weeks after EOT (EOT+4).

Results

Minimal detectable change (MDC) or minimal clinical important difference (MCID) was observed in one or more outcome measures in 8 of 9 participants at EOT and EOT+4 across domains of motor function (67%, 78%), gait speed (78%, 67%), balance confidence (44%, 33%), quality of life (44%, 78%), and dynamic balance (22%, 22%). Discussion. In this case series, 8 of 9 participants showed MDC or MCID changes across multiple functional domains. Improvements were observed immediately post (EOT) and 4-week post-treatment (EOT+4) suggesting a temporal component of the LSVT-BIG impact on functional change. Future research should include clinical trials to examine additional external cueing and task-based intervention efficacy with consideration of intensity, frequency, and mode of delivery across disease severity.

Home-based high-intensity interval training for people with Parkinson's: Protocol for the HIIT-Home4Parkinson's randomized, controlled feasibility study

Background

High-intensity interval training (HIIT) is feasible and beneficial for some people with Parkinson's (PwP), although adherence to extended programs may be problematic. PwP face barriers to exercise such as lack of time, expense, and difficulty with travel logistics due to motor symptoms. HIIT based in the home setting if practical, could therefore be apposite for PwP by overcoming these barriers. However, until now, no home-based HIIT program for PwP has been developed. Cocreated by PwP, clinicians, and family members, the HIIT-Home4Parkinson's (HH4P) program is an innovative, 12-week home-based HIIT program for PwP. This protocol describes a feasibility study designed to assess the feasibility and safety of the HH4P program, explore outcomes that may be sensitive to change, and inform the implementation of a potential full trial.

Methods/design

Using a randomized controlled parallel group design, 24 independently mobile people with Parkinson's of mild to moderate disease severity will be randomized 1:1 to either the HH4P program plus usual care, or usual care alone. Both groups will be assessed at baseline, and upon the completion of the program. Outcomes will include feasibility and safety factors such as recruitment, completion, adverse events, and intervention fidelity with qualitative evaluation along with mechanistic, physiological, and clinical outcomes.

Discussion

Results of this study will inform the rationale and methodological considerations for a full trial with long-term follow-up. Ultimately, further establishing the practicality and utility of home-based HIIT could provide an important exercise option for PwP, potentially leading to extended participation and increased health and well-being for this population.

Association of activities of daily living, mobility and balance ability, and symptoms of Parkinson's disease with the masses and amounts of intramuscular non-contractile tissue of the trunk and lower extremity muscles in patients with Parkinson's disease

PURPOSE

We examined the association of activities of daily living (ADL), mobility and balance ability, and symptoms of Parkinson's disease (PD) with the masses and amounts of intramuscular non-contractile tissue of the trunk and lower extremity muscles in patients with PD.

METHODS

The subjects were 11 community-dwelling patients with PD. ADL were assessed using the Functional Independence Measure. Mobility capacity was assessed based on measurement of maximal walking speed and timed up-and-go time, while balance ability was evaluated based on measurement of one-legged stance time. The symptoms of PD were assessed based on measurement of the Hoehn and Yahr stage and Unified Parkinson's Disease Rating Scale. Muscle thickness (MT) and echo intensity (EI) of the trunk and lower extremity muscles were also measured using an ultrasound imaging device.

RESULTS

Partial correlation analysis revealed an association between reduced ADL and increased EI of the lumbar erector spinae muscle; reduced mobility capacity and increased EI of the rectus abdominis and gluteus minimus muscles; and reduced balance ability and decreased MT of the lumbar erector spinae muscle and increased EI of the lumbar erector spinae, semitendinosus, and tibialis posterior muscles. Partial correlation analysis also showed an association between symptoms of severe PD and decreased MT of the tibialis anterior muscles and increased EI of the lumbar erector spinae, gluteus minimus, and tibialis posterior muscles.

CONCLUSION

The properties of the trunk and lower extremity muscles may be critical for ADL, mobility and balance ability, and symptoms of PD in patients with PD.

Modeling Cues May Reduce Sway Following Sit-To-Stand Transfer for People with Parkinson's Disease

Cues are commonly used to overcome the effects of motor symptoms associated with Parkinson's disease. Little is known about the impact of cues on postural sway during transfers. The objective of this study was to identify if three different types of explicit cues provided during transfers of people with Parkinson's disease results in postural sway more similar to healthy controls. This crossover study had 13 subjects in both the Parkinson's and healthy control groups. All subjects completed three trials of uncued sit to stand transfers. The Parkinson's group additionally completed three trials of sit to stand transfers in three conditions: external attentional focus of reaching to targets, external attentional focus of concurrent modeling, and explicit cue for internal attentional focus. Body worn sensors collected sway data, which was compared between groups with Mann Whitney U tests and between conditions with Friedman's Tests. Sway normalized with modeling but was unchanged in the other conditions. Losses of balance presented with reaching towards targets and cueing for an internal attentional focus. Modeling during sit to stand of people with Parkinson's disease may safely reduce sway more than other common cues.

Efficacy of Tai Chi on lower limb function of Parkinson's disease patients: A systematic review and meta-analysis

Background

At present, the effect of Tai Chi (TC) on lower limb function in patients with Parkinson's disease (PD) is controversial. Therefore, we conducted a meta-analysis on the influence of TC on lower limb function in PD patients.

Methods

According to the PRISMA guidelines, seven databases were searched. Randomized controlled trials (RCTS) were selected and screened according to inclusion and exclusion criteria. We assessed the quality of the studies using the Cochrane Risk of Bias tool and then extracted the characteristics of the included studies. The random effect model was adopted, and heterogeneity was measured by I ² statistic.

Results

A total of 441 articles were screened, and 10 high-quality RCTs were with a total of 532 patients with PD met Our inclusion criteria. Meta-analysis showed that compared To control groups TC improved several outcomes. TC significantly improved motor function (SMD = -0.70; 95% CI = -0.95, -0.45; p < 0.001; I ² = 35%), although The results were not statistically significant for The subgroup analysis of TC duration (SMD = -0.70; 95% CI = -0.95, -0.45; p = 0.88; I ² = 0%;). TC significantly improved balance function (SMD = 0.89; 95% CI = 0.51, 1.27; p < 0.001; I ² = 54%), functional walking capacity (SMD = -1.24; 95% CI = -2.40, -0.09; p = 0.04; I ² = 95%), and gait velocity (SMD = 0.48; 95% CI = -0.02, 0.94; p = 0.04; I ² = 78%), But Did Not improve endurance (SMD = 0.31; 95% CI = -0.12, 0.75; p = 0.16; I ² = 0%), step length (SMD = 0.01; 95% CI = -0.34, 0.37; p = 0.94; I ² = 29%), and cadence (SMD = 0.06; 95% CI = -0.25, 0.36; p = 0.70; I ² = 0%).

Conclusion

TC has beneficial effects on motor function, balance function, functional walking ability, and gait velocity, but does not improve walking endurance, stride length, and cadence.

Ultrasound of the Biceps Muscle in Idiopathic Parkinson's Disease with Deep Brain Stimulation: Rigidity Can Be Quantified by Shear Wave Elastography

Rigidity in Parkinson’s disease (PD) is assessed by clinical scales, mostly the Unified Parkinson’s Disease Rating Scale of the Movement Disorders Society (MDS-UPDRS). While the MDS-UPDRS-III ranges on an integer from 0 to 4, we investigated whether muscle ultrasound shear wave elastography (SWE) offers a refined assessment. Ten PD patients (five treated with deep brain stimulation (DBS) and levodopa, five with levodopa only) and ten healthy controls were included. Over a period of 80 min, both the SWE value and the item 22b-c of the MDS-UPDRS-III were measured at 5 min intervals. The measurements were performed bilaterally at the biceps brachii muscle (BB) and flexor digitorum profundus muscle in flexion and passive extension. Rigidity was modified and tracked under various therapeutic conditions (with and without medication/DBS). The feasibility of SWE for objective quantification was evaluated by correlation with the UPDRS-III: considering all positions and muscles, there was already a weak correlation (r = 0.01, p < 0.001)—in a targeted analysis, the BB in passive extension showed a markedly higher correlation (r = 0.494, p < 0.001). The application of dopaminergic medication and DBS resulted in statistically significant short-term changes in both clinical rigidity and SWE measurements in the BB (p < 0.001). We conclude that rigidity is reflected in the SWE measurements, indicating that SWE is a potential non-invasive quantitative assessment tool for PD.

Parkinson's disease resting tremor severity classification using machine learning with resampling techniques

In resting tremor, the body part is in complete repose and often dampens or subsides entirely with action. The most frequent cause of resting tremors is known as idiopathic Parkinson's disease (PD). For examination, neurologists of patients with PD include tests such as finger-to-nose tests, walking back and forth in the corridor, and the pull test. This evaluation is focused on Unified Parkinson's disease rating scale (UPDRS), which is subjective as well as based on some daily life motor activities for a limited time frame. In this study, severity analysis is performed on an imbalanced dataset of patients with PD. This is the reason why the classification of various data containing imbalanced class distribution has endured a notable drawback of the performance achievable by various standard classification learning algorithms. In this work, we used resampling techniques including under-sampling, over-sampling, and a hybrid combination. Resampling techniques are incorporated with renowned classifiers, such as XGBoost, decision tree, and K-nearest neighbors. From the results, it is concluded that the Over-sampling method performed much better than under-sampling and hybrid sampling techniques. Among the over-sampling techniques, random sampling has obtained 99% accuracy using XGBoost classifier and 98% accuracy using the decision tree. Besides, it is observed that different resampling methods performed differently with various classifiers.

Motor imagery and action-observation in neurorehabilitation: A study protocol in Parkinson's disease patients

Introduction

Action Observation Treatment (AOT) and Motor Imagery (MI) represent very promising cognitive strategies in neuro-rehabilitation. This study aims to compare the effectiveness of the two cognitive strategies, taken alone or combined, in Parkinson's disease patients.

Material and methods

This study is designed as a prospective randomized controlled trial, with four arms. We estimated a sample size of 64 patients (16 in each treatment group) to be able to detect an effect size of F = 0.4 with a statistical significance of 0.05. Primary outcomes will be functional gains in the FIM and UPDRS scales. Secondary outcome measure will be functional gain as revealed by kinematic parameters measured at Gait Analysis.

Discussion

The results of this trial will provide insights into the use of AOT and MI, taken alone or combined, in the rehabilitation of Parkinson's disease patients.

Ethics and dissemination

The study protocol was approved by the Ethics Committee of the Don Gnocchi Foundation. The study will be conducted in accordance with the 1996 World Medical Association guidelines and according to good clinical practice. The study has been registered on clinicaltrial.gov under the following code: AOTPRFDG. Dissemination will include both submission of the study to peer-reviewed journals and discussion of the study protocol at conferences.

Monitoring gait at home with radio waves in Parkinson's disease: A marker of severity, progression, and medication response

Parkinson's disease (PD) is the fastest-growing neurological disease in the world. A key challenge in PD is tracking disease severity, progression, and medication response. Existing methods are semisubjective and require visiting the clinic. In this work, we demonstrate an effective approach for assessing PD severity, progression, and medication response at home, in an objective manner. We used a radio device located in the background of the home. The device detected and analyzed the radio waves that bounce off people's bodies and inferred their movements and gait speed. We continuously monitored 50 participants, with and without PD, in their homes for up to 1 year. We collected over 200,000 gait speed measurements. Cross-sectional analysis of the data shows that at-home gait speed strongly correlates with gold-standard PD assessments, as evaluated by the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III subscore and total score. At-home gait speed also provides a more sensitive marker for tracking disease progression over time than the widely used MDS-UPDRS. Further, the monitored gait speed was able to capture symptom fluctuations in response to medications and their impact on patients' daily functioning. Our study shows the feasibility of continuous, objective, sensitive, and passive assessment of PD at home and hence has the potential of improving clinical care and drug clinical trials.

Feasibility of telemedicine research visits in people with Parkinson's disease residing in medically underserved areas

Introduction

Gait, balance, and cognitive impairment make travel cumbersome for People with Parkinson's disease (PwPD). About 75% of PwPD cared for at the University of Arkansas for Medical Sciences' Movement Disorders Clinic reside in medically underserved areas (MUAs). Validated remote evaluations could help improve their access to care. Our goal was to explore the feasibility of telemedicine research visits for the evaluation of multi-modal function in PwPD in a rural state.

Methods

In-home telemedicine research visits were performed in PwPD. Motor and non-motor disease features were evaluated and quantified by trained personnel, digital survey instruments for self-assessments, digital voice recordings, and scanned and digitized Archimedes spiral drawings. Participant's MUA residence was determined after evaluations were completed.

Results

Twenty of the fifty PwPD enrolled resided in MUAs. The groups were well matched for disease duration, modified motor UPDRS, and Montreal Cognitive assessment scores but MUA participants were younger. Ninety-two percent were satisfied with their visit, and 61% were more likely to participate in future telemedicine research. MUA participants traveled longer distances, with higher travel costs, lower income, and education level. While 50% of MUA participants reported self-reliance for in-person visits, 85% reported self-reliance for the telemedicine visit. We rated audio-video quality highly in approximately 60% of visits in both groups. There was good correlation with prior in-person research assessments in a subset of participants.

Conclusions

In-home research visits for PwPD in MUAs are feasible and could help improve access to care and research participation in these traditionally underrepresented populations.

Deep Learning for Daily Monitoring of Parkinson's Disease Outside the Clinic Using Wearable Sensors

Now that wearable sensors have become more commonplace, it is possible to monitor individual healthcare-related activity outside the clinic, unleashing potential for early detection of events in diseases such as Parkinson's disease (PD). However, the unsupervised and "open world" nature of this type of data collection make such applications difficult to develop. In this proof-of-concept study, we used inertial sensor data from Verily Study Watches worn by individuals for up to 23 h per day over several months to distinguish between seven subjects with PD and four without. Since motor-related PD symptoms such as bradykinesia and gait abnormalities typically present when a PD subject is walking, we initially used human activity recognition (HAR) techniques to identify walk-like activity in the unconstrained, unlabeled data. We then used these "walk-like" events to train one-dimensional convolutional neural networks (1D-CNNs) to determine the presence of PD. We report classification accuracies near 90% on single 5-s walk-like events and 100% accuracy when taking the majority vote over single-event classifications that span a duration of one day. Though based on a small cohort, this study shows the feasibility of leveraging unconstrained wearable sensor data to accurately detect the presence or absence of PD.

Measurement tools to assess activities of daily living in patients with Parkinson's disease: A systematic review

Introduction

Parkinson's disease (PD) is associated with a progressive inability to accomplish essential activities of daily living (ADL) resulting in a loss of autonomy and quality of life. Accurate measurement of ADL in PD is important to monitor disease progression and optimize care. Despite its relevance, it is still unclear which measurement instruments are the most suitable for evaluating ADL in people with PD.

Objective

To identify and critically appraise which measurement instruments have been used to assess ADL in PD.

Methods

A systematic review was conducted using the databases CENTRAL, MEDLINE, and PEDro from their inception to October 2021 to identify all observational and experimental studies conducted in PD or atypical parkinsonism that included an ADL assessment. Titles and abstracts were screened independently by two authors. The clinimetric properties of the measurement instruments were assessed, and the instruments were classified as "recommended," "suggested," or "listed."

Results

A total of 129 articles were included, with 37 measurement instruments used. The Unified Parkinson's Disease Rating Scale (UPDRS), the Schwab & England ADL scale (S&E scale), the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS), the Barthel Index, the Lawton-Brody Instrumental Activities of Daily Living Scale, the Functional Independence Measure (FIM) and the Alzheimer's Disease Cooperative Study - ADL (ADCS-ADL) scale were the seven most frequently cited measurement instruments. Of these, only two included an assessment of basic and instrumental ADL.

Conclusion

MDS-UPDRS and the S&E scale were the only two scales that could be classified as recommended. For the MDS-UPDRS, either the full version or only Part II, which is focused on ADL, can be used. Future studies should explore the use of wearable devices to assess ADL remotely and more continuously.

Sensor Verification and Analytical Validation of Algorithms to Measure Gait and Balance and Pronation/Supination in Healthy Volunteers

Numerous studies have sought to demonstrate the utility of digital measures of motor function in Parkinson’s disease. Frameworks, such as V3, document digital measure development: technical verification, analytical and clinical validation. We present the results of a study to (1) technically verify accelerometers in an Apple iPhone 8 Plus and ActiGraph GT9X versus an oscillating table and (2) analytically validate software tasks for walking and pronation/supination on the iPhone plus passively detect walking measures with the ActiGraph in healthy volunteers versus human raters. In technical verification, 99.4% of iPhone and 91% of ActiGraph tests show good or excellent agreement versus the oscillating table as the gold standard. For the iPhone software task and algorithms, intraclass correlation coefficients (ICCs) > 0.75 are achieved versus the human raters for measures when walking distance is >10 s and pronation/supination when the arm is rotated more than two times. Passively detected walking start and end time was accurate to approx. 1 s and walking measures were accurate to one unit, e.g., one step. The results suggest that the Apple iPhone and ActiGraph GT9X accelerometers are fit for purpose and that task and passively collected measures are sufficiently analytically valid to assess usability and clinical validity in Parkinson’s patients.

Potential of Whole-Body Vibration in Parkinson’s Disease: A Systematic Review and Meta-Analysis of Human and Animal Studies

Simple Summary

Exercise has shown to have a positive impact on both motor and non-motor functions in Parkinson’s Disease patients. However, particularly in later stages of the disease, reduced cognitive function and motor capacity may lead to an inability to stay physically active. Therefore, alternative strategies for patients with Parkinson’s Disease are necessary to minimize burden for patients, their families and public health care. Whole-Body Vibration could be such an alternative. Whole-Body Vibration is an exercise or treatment method in which subjects are exposed to a mechanical vibration while sitting, standing or exercising on a vibrating platform. Whole-Body Vibration is currently used for physiotherapy, sports and rehabilitation purposes. Whole-Body Vibration treatment is interesting because it affects both the body and brain. The potential of Whole-Body Vibration for, specifically, Parkinson’s Disease patients should be clarified for further application. For this purpose, we conducted an extensive systematic review of the articles investigating the effects of Whole-Body Vibrations (1) on animals and humans with Parkinson’s Disease and (2) on neuropathological Parkinson’s Disease mechanisms. The results show some potential of Whole-Body Vibration for Parkinson’s Disease patients. The recommendations provided by this review can be used by researchers and rehabilitative practitioners implementing Whole-Body Vibration as a treatment for Parkinson’s Disease patients.

Abstract

(1) Background: When the severity of Parkinson’s Disease (PD) increases, patients often have difficulties in performing exercises. Whole-Body Vibration (WBV) may be a suitable alternative. This systematic review aims to clarify if WBV shows potential as rehabilitative therapy for PD patients. (2) Methods: We searched several databases for controlled trials investigating the effects of WBV (1) on PD populations and (2) PD neuropathological mechanisms. We included both human and animal studies and performed meta-analyses. (3) Results: The studies on PD populations (14 studies) show an overall significant, but small, effect in favor of WBV (Hedges’ g = 0.28), for which the effects on stability (Hedges’ g = 0.39) and balance (Hedges’ g = 0.30) are the most prominent. The studies on the neuropathological mechanisms (18 studies) show WBV effects on neuroinflammation (Hedges’ g = –1.12) and several specific WBV effects on neurotransmitter systems, growth factors, neurogenesis, synaptic plasticity and oxidative stress. (4) Conclusions: The effects of WBV on human PD patients remains inconclusive. Nevertheless, WBV protocols with sufficient duration (≥3 weeks), session frequency (≥3 sessions/week) and vibration frequency (≥20 Hz) show potential as a treatment method, especially for motor function. The potential of WBV for PD patients is confirmed by the effects on the neuropathological mechanisms in mostly non-PD populations. We recommend high-quality future studies on both PD patients and PD mouse models to optimize WBV protocols and to examine the neuropathological mechanisms in PD populations.

Watching Parkinson's disease with wrist-based sensors

Parkinson's disease (PD) lacks sensitive, objective, and reliable measures for disease progression and response. This presents a challenge for clinical trials given the multifaceted and fluctuating nature of PD symptoms. Innovations in digital health and wearable sensors promise to more precisely measure aspects of patient function and well-being. Beyond research trials, digital biomarkers and clinical outcome assessments may someday support clinician-initiated or closed-loop treatment adjustments. A recent study from Verily Life Sciences presents results for a smartwatch-based motor exam intended to accelerate the development and evaluation of therapies for PD.

A composite clinical motor score as a comprehensive and sensitive outcome measure for Parkinson's disease

BACKGROUND

An unmet need remains for sensitive outcome measures in neuroprotective trials. The study aims to determine whether a composite clinical motor score, combining the Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) III motor examination score, Purdue Pegboard Test, and Timed Up and Go, provides greater sensitivity in detecting motor change in early disease than the MDS-UPDRS III alone.

METHODS

The Oxford Discovery longitudinal cohort study involves individuals with isolated rapid eye movement sleep behaviour disorder (iRBD) (n=272, confirmed polysomnographically, median follow-up: 1.6 years), idiopathic Parkinson's disease (PD) (n=909, median follow-up: 3.5 years, baseline: <3.5 years disease duration) and controls (n=316, age-matched and sex-matched, without a first-degree family history of PD). Motor and non-motor assessments were performed at each in-person visit.

RESULTS

Compared with the MDS-UPDRS III, the composite clinical motor score demonstrated a wider score distribution in iRBD and controls, lower coefficient of variation (37% vs 67%), and higher correlation coefficients with self-reported measures of motor severity (0.65 vs 0.61) and overall health status (-0.40 vs -0.33). Greater score range in mild to moderate PD, higher magnitude of longitudinal change in iRBD and longitudinal score linearity suggest better sensitivity in detecting subtle motor change. The composite clinical motor score was more accurate than the MDS-UPDRS III in predicting clinical outcomes, requiring 64% fewer participants with PD and 51% fewer participants with iRBD in sample size estimations for a hypothetical 18-month placebo-controlled clinical trial.

CONCLUSION

The composite clinical motor score may offer greater consistency and sensitivity in detecting change than the MDS-UPDRS III.

Virtual exam for Parkinson's disease enables frequent and reliable remote measurements of motor function

Sensor-based remote monitoring could help better track Parkinson's disease (PD) progression, and measure patients' response to putative disease-modifying therapeutic interventions. To be useful, the remotely-collected measurements should be valid, reliable, and sensitive to change, and people with PD must engage with the technology. We developed a smartwatch-based active assessment that enables unsupervised measurement of motor signs of PD. Participants with early-stage PD (N = 388, 64% men, average age 63) wore a smartwatch for a median of 390 days. Participants performed unsupervised motor tasks both in-clinic (once) and remotely (twice weekly for one year). Dropout rate was 5.4%. Median wear-time was 21.1 h/day, and 59% of per-protocol remote assessments were completed. Analytical validation was established for in-clinic measurements, which showed moderate-to-strong correlations with consensus MDS-UPDRS Part III ratings for rest tremor (⍴ = 0.70), bradykinesia (⍴ = -0.62), and gait (⍴ = -0.46). Test-retest reliability of remote measurements, aggregated monthly, was good-to-excellent (ICC = 0.75-0.96). Remote measurements were sensitive to the known effects of dopaminergic medication (on vs off Cohen's d = 0.19-0.54). Of note, in-clinic assessments often did not reflect the patients' typical status at home. This demonstrates the feasibility of smartwatch-based unsupervised active tests, and establishes the analytical validity of associated digital measurements. Weekly measurements provide a real-life distribution of disease severity, as it fluctuates longitudinally. Sensitivity to medication-induced change and improved reliability imply that these methods could help reduce sample sizes needed to demonstrate a response to therapeutic interventions or disease progression.

Progression of Self-Perceived Speech and Swallowing Impairment in Early Stage Parkinson's Disease: Longitudinal Analysis of the Unified Parkinson's Disease Rating Scale

PURPOSE

The purpose of this study was to investigate the presence and progression of self-perceived speech and swallowing impairments in newly diagnosed people with Parkinson's disease (PD) longitudinally across 6 years.

METHOD

Longitudinal data from the Parkinson's Progression Markers Initiative were analyzed across six consecutive years in a cohort of 269 newly diagnosed people with PD, and a subset of those (n = 211) who were assessed at every time point across the 6 years. Dependent variables included self-perceived ratings of speech and swallowing impairment severity from the Unified Parkinson's Disease Rating Scale. Patient-centered factors of age at diagnosis and motor phenotype were also assessed to determine if they were related to the change in self-perceived speech and swallowing impairments.

RESULTS

Overall, self-perceived speech and swallowing impairments were present in newly diagnosed people with PD, although over time, the degree of severity for both remained in the mild range. However, the rate of change over time was significant for perceived speech impairment, F(5.5, 1158.8) = 21.1, p < .001), and perceived swallowing impairment, F(5.2, 1082.6) = 8.6, p < .001. Changes for speech and swallowing impairment were both in the direction of progressive severity. There were no effects of age at diagnosis or motor phenotype on the degree of change for either speech or swallowing.

CONCLUSIONS

Self-perceptions of speech and swallowing impairment changed significantly over time in newly diagnosed people with PD (PWPD). Consistent with existing literature, self-perceptions of speech impairment were rated as more severe than those of swallowing impairment. These findings reveal that even in the early years postdiagnoses, PWPD are experiencing changes to speech and swallowing function, albeit within the mildly severe range. The presence of self-perceived mild speech and swallowing impairments in the initial years postdiagnosis may support the need for intervention to improve and or sustain function over time.

The Effect of Whole-Body Vibration on Proprioception and Motor Function for Individuals with Moderate Parkinson Disease: A Single-Blind Randomized Controlled Trial

Introduction

Previous studies have shown that whole-body vibration (WBV) may have a potential impact on gait and balance in individuals with Parkinson's disease (PD). However, this body of work has proven inconclusive due to the diverse disease progression and broad age range associated with PD. The effects of WBV on proprioception, a sense frequently affected by PD, has rarely been studied.

Objective

To investigate the short-term effect of WBV on proprioception and motor function for individual with moderate PD.

Design

A single-blind randomized controlled trial. Setting. A hospital and a laboratory. Participants. 32 participants with moderate PD were recruited and randomly assigned into either the WBV or conventional therapy groups. Interventions. For the WBV group, each treatment session included five, one-minute bouts of whole-body vibration paired with one-minute rest (frequency: 6 Hz; amplitude: 3 mm). Each conventional therapy participant received balance and mobility training for 10 minutes. Main Outcome Measures. Outcome measures included proprioceptive sensitivity of the upper limb, position sense of the knee joint, Unified Parkinson's disease rating scale : motor section (UPDRS-motor), functional reach test (FRT), and the timed up and go test (TUG).

Results

No statistically significant difference was found between groups. However, both groups showed a significant improvement in motor function after treatment, including UPDRS-motor (P = 0.04), less affected side of FRT (P = 0.019), and TUG (P = 0.006).

Conclusions

Although the effect of WBV was not superior to the conventional therapy, it provided a passive and safe clinical intervention as an alternative treatment, especially for individuals with motor impairment or poor balance function.

An Evaluation of KELVIN, an Artificial Intelligence Platform, as an Objective Assessment of the MDS UPDRS Part III

BACKGROUND

Parkinson's disease severity is typically measured using the Movement Disorder Society Unified Parkinson's disease rating scale (MDS-UPDRS). While training for this scale exists, users may vary in how they score a patient with the consequence of intra-rater and inter-rater variability.

OBJECTIVE

In this study we explored the consistency of an artificial intelligence platform compared with traditional clinical scoring in the assessment of motor severity in PD.

METHODS

Twenty-two PD patients underwent simultaneous MDS-UPDRS scoring by two experienced MDS-UPDRS raters and the two sets of accompanying video footage were also scored by an artificial intelligence video analysis platform known as KELVIN.

RESULTS

KELVIN was able to produce a summary score for 7 MDS-UPDRS part 3 items with good inter-rater reliability (Intraclass Correlation Coefficient (ICC) 0.80 in the OFF-medication state, ICC 0.73 in the ON-medication state). Clinician scores had exceptionally high levels of inter-rater reliability in both the OFF (0.99) and ON (0.94) medication conditions (possibly reflecting the highly experienced team). There was an ICC of 0.84 in the OFF-medication state and 0.31 in the ON-medication state between the mean Clinician and mean Kelvin scores for the equivalent 7 motor items, possibly due to dyskinesia impacting on the KELVIN scores.

CONCLUSION

We conclude that KELVIN may prove useful in the capture and scoring of multiple items of MDS-UPDRS part 3 with levels of consistency not far short of that achieved by experienced MDS-UPDRS clinical raters, and is worthy of further investigation.

Automated and accurate assessment for postural abnormalities in patients with Parkinson's disease based on Kinect and machine learning

Background

Automated and accurate assessment for postural abnormalities is necessary to monitor the clinical progress of Parkinson’s disease (PD). The combination of depth camera and machine learning makes this purpose possible.

Methods

Kinect was used to collect the postural images from 70 PD patients. The collected images were processed to extract three-dimensional body joints, which were then converted to two-dimensional body joints to obtain eight quantified coronal and sagittal features (F1-F8) of the trunk. The decision tree classifier was carried out over a data set established by the collected features and the corresponding doctors’ MDS-UPDRS-III 3.13 (the 13th item of the third part of Movement Disorder Society-Sponsored Revision of the Unified Parkinson’s Disease Rating Scale) scores. An objective function was implanted to further improve the human–machine consistency.

Results

The automated grading of postural abnormalities for PD patients was realized with only six selected features. The intraclass correlation coefficient (ICC) between the machine’s and doctors’ score was 0.940 (95%CI, 0.905–0.962), meaning the machine was highly consistent with the doctors’ judgement. Besides, the decision tree classifier performed outstandingly, reaching 90.0% of accuracy, 95.7% of specificity and 89.1% of sensitivity in rating postural severity.

Conclusions

We developed an intelligent evaluation system to provide accurate and automated assessment of trunk postural abnormalities in PD patients. This study demonstrates the practicability of our proposed method in the clinical scenario to help making the medical decision about PD.

Effects of dry needling on gait and muscle tone in Parkinson's disease: a randomized clinical trial

BACKGROUND

Alterations in gait and muscular rigidity are common and disabling in persons with Parkinson's disease (PD).

OBJECTIVE

The aim of this study was to determine whether a single dry needling (DN) session can promote changes in gait and muscle tone in the lower extremities as well as in the evolution of the disease in persons with PD.

METHODS

A randomized double-blind clinical trial was designed. Participants were randomly assigned to an intervention group (IG) that received a session of DN over the semitendinosus, medial gastrocnemius, soleus and rectus femoris muscles, or to a control group (CG) that received a session of sham DN in the same muscles. The effects of DN were assessed using the timed up and go test (TUG), 10 meter walk test (10MWT), 6 minute walk test (6MWT) and myotonometry before, immediately after, and 7 days after the intervention.

RESULTS

Thirty-three participants were analyzed aged 69.9 ± 7.2 years (mean ± SD; 39% female). There were no significant differences between the IG and CG for any outcomes. Significant differences were observed when comparing the Pre and Follow-up values in the IG for functional mobility of gait in the TUG (p = 0.049), gait speed in the 10MWT (p = 0.041) and muscle tone in the lower extremities by myotonometry (frequency (p = 0.027) and stiffness (p = 0.013)). By comparison, there were no significant within-group differences in the CG.

CONCLUSION

A single session of DN had no measurable benefit compared to a single session of sham DN. Within-group changes in the IG suggested improvements in functional mobility of gait and gait speed, as well as changes in the muscle tone in the lower extremities of PD patients, which could be worthy of further exploration by future research.

Boxing vs Sensory Exercise for Parkinson's Disease: A Double-Blinded Randomized Controlled Trial

Background. Exercise is increasingly becoming recognized as an important adjunct to medications in the clinical management of Parkinson's disease (PD). Boxing and sensory exercise have shown immediate benefits, but whether they continue beyond program completion is unknown. This study aimed to investigate the effects of boxing and sensory training on motor symptoms of PD, and whether these benefits remain upon completion of the intervention. Methods. In this 20-week double-blinded randomized controlled trial, 40 participants with idiopathic PD were randomized into 2 treatment groups, (n = 20) boxing or (n = 20) sensory exercise. Participants completed 10 weeks of intervention. Motor symptoms were assessed at (week 0, 10, and 20) using the Unified Parkinson's Disease Rating Scale (UPDRS-III). Data were analyzed using SPSS, and repeated-measures ANOVA was conducted. Results. A significant interaction effect between groups and time were observed F(1, 39) = 4.566, P = .036, where the sensory group improved in comparison to the boxing group. Post hoc analysis revealed that in comparison to boxing, the effects of exercise did not wear off at washout (week 20) P < .006. Conclusion. Future rehabilitation research should incorporate similar measures to explore whether effects of exercise wear off post intervention.

Comparison of the Parkinson's KinetiGraph to off/on levodopa response testing: Single center experience

BACKGROUND AND OBJECTIVE

Levodopa off/on testing is frequently performed to assess medication response in patients with Parkinson's disease (PD) as an aid in determining best medical management or potential surgical candidacy. The Parkinson's Kinetigraph (PKG) is a wearable device which generates tremor, bradykinesia (BKS) and dyskinesia (DKS) scores representing motor symptoms over a six-day period. In this study, we compared off/on testing with PKG motor scores.

METHODS

Patients were enrolled as part of an observational study: Assessing the Longitudinal Signs in PD, a three-year study evaluating clinical and biomarker evolution in patients with PD taking levodopa. Patients underwent off/on testing at baseline and 6-month visits. A greater than 30% improvement between off and on MDS-Unified Parkinson's Disease Rating Scale scores was considered a robust response. After each visit, patients wore the PKG for 6 days. A bradykinesia score (BKS) greater than 26 and dyskinesia score (DKS) greater than 9 were considered poorly controlled bradykinesia and dyskinesia, respectively.

RESULTS

The median BKS at the baseline and 6-month visits were 27.15 and 27.55, respectively, despite a robust median off/on improvement at both visits. In addition, 10/18 (66%) and 7/13 (53.8%) patients with robust off/on improvement at the baseline and 6-month visits, respectively, demonstrated a BKS > 26 or DKS > 9.

CONCLUSION

A robust off/on response during a clinic visit does not necessarily reflect adequately controlled motor symptoms. The PKG, by virtue of its continuous recording of motor movements, may provide additional clinically relevant data on motor symptoms which may be useful for prospective observational studies.

Nutritional Ketosis in Parkinson's Disease - a Review of Remaining Questions and Insights

Nutritional ketosis has promise for treating Parkinson's disease. Three previous studies explored the use of a ketogenic diet in cohorts with Parkinson's disease, and, while not conclusive, the data suggest non-motor symptom benefit. Before the ketogenic diet can be considered as a therapeutic option, it is important to establish with greater certainty that there is a reliable symptomatic benefit: which symptoms or groups of symptoms are impacted (if non-motor symptoms, which ones, and by which mechanism), what timescale is needed to obtain benefit, and how large an effect size can be achieved? To accomplish this, further investigation into the disease mechanisms based on pre-clinical data and hints from the clinical outcomes to date is useful to understand target engagement and gauge which mechanism could lead to a testable hypothesis. We review research pertaining to ketogenic diet, exogenous ketones, fasting, clinical studies, and theoretical review papers regarding therapeutic mechanisms from direct ketone body signaling and indirect metabolic effects. Through discussion of these findings and consideration of whether the ketogenic diet can be regarded as therapeutically useful for adjunctive therapy for Parkinson's disease, we identify remaining questions for the clinician to consider prior to recommending this diet.

Effect of Lee Silverman Voice Treatment (LSVT)® BIG on motor symptoms in a patient with severe Parkinson's disease: a case report

Introduction: Lee Silverman Voice Treatment® BIG (LSVT® BIG) is widely used to improve motor symptoms in patients with mild-to-moderate Parkinson's disease (PD).Objective: To describe the effect of LSVT® BIG on the motor symptoms of a patient with severe PD.Case Description: A 77-year-old woman who was diagnosed with PD received a 4-week LSVT® BIG program under the supervision of certified LSVT® BIG physical therapists. Her disease severity was classified as Hoehn and Yahr stage 4. The unified Parkinson's disease rating scale (UPDRS) part 3, 10-m walk test (10MWT), timed up-and-go test (TUG), Berg balance scale (BBS), and 30-s chair stand test (30-s CST) were used for assessment before and after intervention.Outcomes: The UPDRS part 3, 10MWT, TUG, BBS, and 30-s CST improved after intervention (33 to 26, 0.51 to 0.69 m/s, 38.1 to 23.2 seconds, 11 to 34, and 3 to 9 times, respectively). All improvements exceeded the Minimal Clinically Important Difference or Minimal Detectable Change values (2.5, 0.16 m/s, 3.5 seconds, 5, and 3 times, respectively).Conclusions: These results indicated that LSVT® BIG appears to have improved motor symptoms in a patient with severe PD. Further studies, ideally randomized controlled trials, are needed to confirm these findings.

Periodized Resistance Training With and Without Functional Training Improves Functional Capacity, Balance, and Strength in Parkinson's Disease

ABSTRACT

Strand, KL, Cherup, NP, Totillo, MC, Castillo, DC, Gabor, NJ, and Signorile, JF. Periodized resistance training with and without functional training improves functional capacity, balance, and strength in Parkinson's disease. J Strength Cond Res 35(6): 1611-1619, 2021-Periodized progressive resistance training (PRT) is a common method used to improve strength in persons with Parkinson's disease (PD). Many researchers advocate the addition of functional training to optimize translation to activities of daily living; however, machine-based PRT, using both force and velocity training components, may elicit similar benefits. Thirty-five persons with PD (Hoehn and Yahr I-III) were randomized into a strength, power, and hypertrophy (SPH; n = 17) or strength, power, and functional (SP + Func; n = 18) group, training 3 times weekly for 12 weeks. Both groups performed machine-based strength and power training on days 1 and 2 each week, respectively; whereas, on day 3, SPH group performed machine-based hypertrophy training and SP + Func group performed functional training. Functional performance was tested using the timed up and go, 30-second sit-to-stand (30-s STS), gallon-jug shelf-transfer, and seated medicine ball throw (SMBT) tests. Balance (Mini-BESTest), strength, motor symptoms (UPDRS-III), quality of life, and freezing of gait (FOG) were also assessed. Repeated measures analysis of variance revealed a main effect for time (p ≤ 0.05) with significant improvements for the sample in the 30-s STS (p = 0.002), SMBT (p = 0.003), Mini-BESTest (p < 0.001), upper-body strength (p = 0.002) and lower-body strength (p < 0.001). A significant group × time interaction was seen for FOG, with SP + Func alone showing improvement (p = 0.04). Furthermore, the SPH group produced a clinically important difference for the UPDRS-III (mean difference = 4.39, p = 0.18). We conclude that both exercise strategies can be equally effective at improving functional capacity, balance, and muscular strength in individuals with PD. In addition, FOG and motor symptoms may be targeted through SP + Func and SPH, respectively. The results provide options for individualized exercise prescriptions.

Machine Learning-Based Automatic Rating for Cardinal Symptoms of Parkinson Disease

OBJECTIVE

We developed and investigated the feasibility of a machine learning-based automated rating for the 2 cardinal symptoms of Parkinson disease (PD): resting tremor and bradykinesia.

METHODS

Using OpenPose, a deep learning-based human pose estimation program, we analyzed video clips for resting tremor and finger tapping of the bilateral upper limbs of 55 patients with PD (110 arms). Key motion parameters, including resting tremor amplitude and finger tapping speed, amplitude, and fatigue, were extracted to develop a machine learning-based automatic Unified Parkinson's Disease Rating Scale (UPDRS) rating using support vector machine (SVM) method. To evaluate the performance of this model, we calculated weighted κ and intraclass correlation coefficients (ICCs) between the model and the gold standard rating by a movement disorder specialist who is trained and certified by the Movement Disorder Society for UPDRS rating. These values were compared to weighted κ and ICC between a nontrained human rater and the gold standard rating.

RESULTS

For resting tremors, the SVM model showed a very good to excellent reliability range with the gold standard rating (κ 0.791; ICC 0.927), with both values higher than that of nontrained human rater (κ 0.662; ICC 0.861). For finger tapping, the SVM model showed a very good reliability range with the gold standard rating (κ 0.700 and ICC 0.793), which was comparable to that for nontrained human raters (κ 0.627; ICC 0.797).

CONCLUSION

Machine learning-based algorithms that automatically rate PD cardinal symptoms are feasible, with more accurate results than nontrained human ratings.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that machine learning-based automated rating of resting tremor and bradykinesia in people with PD has very good reliability compared to a rating by a movement disorder specialist.

Influence of Striatal Dopamine, Cerebral Small Vessel Disease, and Other Risk Factors on Age-Related Parkinsonian Motor Signs

OBJECTIVE

Parkinsonian motor signs are common and disabling in older adults without Parkinson's disease (PD), but its risk factors are not completely understood. We assessed the influence of striatal dopamine levels, cerebral small vessel disease, and other factors on age-related parkinsonian motor signs in non-PD adults.

METHODS

Striatal dopamine transporter (DAT) binding was quantified via [11C]-CFT positron emission tomography in 87 neurologically intact adults (20-85 years, 57.47% female) with concurrent data on: Unified Parkinson's Disease Rating Scale motor (UPDRSm), white matter hyperintensities (WMH), and other risk factors (grip strength, vibratory sensitivity, cardio- and cerebro-vascular comorbidities). Sex-adjusted nonparametric models first estimated the associations of age, DAT, WMH, and other factors with UPDRSm; next, interactions of age by DAT, WMH, or other factors were tested. To quantify the influence of DAT, WMH, and other risk factors on the main association of age with UPDRSm, multivariable mediation models with bootstrapped confidence intervals (CI) were used.

RESULTS

Older age, lower DAT, higher WMH, and worse risk factors significantly predicted worse UPDRSm (sex-adjusted p < .04 for all). DAT, but not WMH or other factors, positively and significantly interacted with age (p = .02). DAT significantly reduced the age-UPDRSm association by 30% (results of fully adjusted mediation model: indirect effect: 0.027; bootstrapped 95% CI: 0.0007, 0.074).

CONCLUSIONS

Striatal dopamine appears to influence to some extent the relationship between age and parkinsonian signs. However, much of the variance of parkinsonian signs appears unexplained. Longitudinal studies to elucidate the multifactorial causes of this common condition of older age are warranted.

Cross-frequency coupling between gamma oscillations and deep brain stimulation frequency in Parkinson's disease

The disruption of pathologically enhanced beta oscillations is considered one of the key mechanisms mediating the clinical effects of deep brain stimulation on motor symptoms in Parkinson's disease. However, a specific modulation of other distinct physiological or pathological oscillatory activities could also play an important role in symptom control and motor function recovery during deep brain stimulation. Finely tuned gamma oscillations have been suggested to be prokinetic in nature, facilitating the preferential processing of physiological neural activity. In this study, we postulate that clinically effective high-frequency stimulation of the subthalamic nucleus imposes cross-frequency interactions with gamma oscillations in a cortico-subcortical network of interconnected regions and normalizes the balance between beta and gamma oscillations. To this end we acquired resting state high-density (256 channels) EEG from 31 patients with Parkinson's disease who underwent deep brain stimulation to compare spectral power and power-to-power cross-frequency coupling using a beamformer algorithm for coherent sources. To show that modulations exclusively relate to stimulation frequencies that alleviate motor symptoms, two clinically ineffective frequencies were tested as control conditions. We observed a robust reduction of beta and increase of gamma power, attested in the regions of a cortical (motor cortex, supplementary motor area, premotor cortex) and subcortical network (subthalamic nucleus and cerebellum). Additionally, we found a clear cross-frequency coupling of narrowband gamma frequencies to the stimulation frequency in all of these nodes, which negatively correlated with motor impairment. No such dynamics were revealed within the control posterior parietal cortex region. Furthermore, deep brain stimulation at clinically ineffective frequencies did not alter the source power spectra or cross-frequency coupling in any region. These findings demonstrate that clinically effective deep brain stimulation of the subthalamic nucleus differentially modifies different oscillatory activities in a widespread network of cortical and subcortical regions. Particularly the cross-frequency interactions between finely tuned gamma oscillations and the stimulation frequency may suggest an entrainment mechanism that could promote dynamic neural processing underlying motor symptom alleviation.

Analyzing the effects of PDSAFEx™ on the motor symptoms of Parkinson's disease: A retrospective study

BACKGROUND

The cardinal motor symptoms of Parkinson's disease (PD) include postural instability, bradykinesia, tremor and rigidity. The overall Unified Parkinson's Disease Rating Scale (UPDRS-III) indicates, the gold-standard treatment for PD (dopaminergic-therapy) is very effective in improving these symptoms. However, recent research indicated that 2 of the 4 cardinal symptoms of PD (balance and tremor) remain unimproved by dopaminergic-therapy. This prompts the investigation of other alternative and adjunct treatments such as exercise rehabilitation. Unfortunately, like drug studies, exercise studies often focus on overall symptom improvement yet fail to monitor changes to specific symptoms. This may be problematic for individuals with different symptomatic phenotypes. If tremor/balance were the main concern, then adjunct therapies may be critically important when these symptoms may be dopa-resistant. Thus, it is important for all therapies to examine individual symptomatic-improvement. Interestingly, recent studies show PDSAFEx™ (a sensory integration therapy) to have a significantly improve motor symptoms in comparison to traditional exercise (14). Yet, the effects of PDSAFEx™ on individual PD symptoms is unknown.

OBJECTIVE

To explore the effects of PDSAFEx™ on PD symptoms in adjunct to medications.

METHODS

UPDRS-III scores of 229 cases were retrospectively examined and analysed in SPSS using Wilcoxon pairs singed-rank test to evaluate specific symptom-improvements.

RESULTS

PDSAFEx™ was confirmed to improve overall motor symptoms (p = 0.0001), but more importantly a significant improvement to tremor (p < 0.00001) and balance (p < 0.00001) were also identified.

CONCLUSIONS

These findings suggest that PDSAFEx™ is an important adjunct to medications, since it is able to address all four cardinal symptoms of PD.

Parkinson's disease: current assessment methods and wearable devices for evaluation of movement disorder motor symptoms - a patient and healthcare professional perspective

BACKGROUND

Parkinson's disease is the second most common long-term chronic, progressive, neurodegenerative disease, affecting more than 10 million people worldwide. There has been a rising interest in wearable devices for evaluation of movement disorder diseases such as Parkinson's disease due to the limitations in current clinic assessment methods such as Unified Parkinson's Disease Rating Scale (UPDRS) and the Hoehn and Yahr (HY) scale. However, there are only a few commercial wearable devices available, which, in addition, have had very limited adoption and implementation. This inconsistency may be due to a lack of users' perspectives in terms of device design and implementation. This study aims to identify the perspectives of healthcare professionals and patients linked to current assessment methods and to identify preferences, and requirements of wearable devices.

METHODS

This was a qualitative study using semi-structured interviews followed by focus groups. Transcripts from sessions were analysed using an inductive thematic approach.

RESULTS

It was noted that the well-known assessment process such as Unified Parkinson's Disease Rating Scale (UPDRS) was not used routinely in clinics since it is time consuming, subjective, inaccurate, infrequent and dependent on patients' memories. Participants suggested that objective assessment methods are needed to increase the chance of effective treatment. The participants' perspectives were positive toward using wearable devices, particularly if they were involved in early design stages. Patients emphasized that the devices should be comfortable, but they did not have any concerns regarding device visibility or data privacy transmitted over the internet when it comes to their health. In terms of wearing a monitor, the preferable part of the body for all participants was the wrist. Healthcare professionals stated a need for an economical solution that is easy to interpret. Some design aspects identified by patients included clasps, material choice, and form factor.

CONCLUSION

The study concluded that current assessment methods are limited. Patients' and healthcare professionals' involvement in wearable devices design process has a pivotal role in terms of ultimate user acceptance. This includes the provision of additional functions to the wearable device, such as fall detection and medication reminders, which could be attractive features for patients.

Multi-Dimensional, Short-Timescale Quantification of Parkinson's Disease and Essential Tremor Motor Dysfunction

Introduction: Parkinson's disease (PD) is a progressive movement disorder characterized by heterogenous motor dysfunction with fluctuations in severity. Objective, short-timescale characterization of this dysfunction is necessary as therapies become increasingly adaptive.

Objectives: This study aims to characterize a novel, naturalistic, and goal-directed tablet-based task and complementary analysis protocol designed to characterize the motor features of PD.

Methods: A total of 26 patients with PD and without deep brain stimulation (DBS), 20 control subjects, and eight patients with PD and with DBS completed the task. Eight metrics, each designed to capture an aspect of motor dysfunction in PD, were calculated from 1-second, non-overlapping epochs of the raw positional and pressure data captured during task completion. These metrics were used to generate a classifier using a support vector machine (SVM) model to produce a unifying, scalar “motor error score” (MES). The data generated from these patients with PD were compared to same-day standard clinical assessments. Additionally, these data were compared to analogous data generated from a separate group of 12 patients with essential tremor (ET) to assess the task's specificity for different movement disorders. Finally, an SVM model was generated for each of the eight patients with PD and with DBS to differentiate between their motor dysfunction in the “DBS On” and “DBS Off” stimulation states.

Results: The eight metrics calculated from the raw positional and force data captured during task completion were non-redundant. MES generated by the SVM analysis protocol showed a strong correlation with MDS-UPDRS-III scores assigned by movement disorder specialists. Analysis of the relative contributions of each of the eight metrics showed a significant difference between the motor dysfunction of PD and ET. Much of this difference was attributable to the homogenous, tremor-dominant phenotype of ET motor dysfunction. Finally, in individual patients with PD with DBS, task performance and subsequent SVM classification effectively differentiated between the “DBS On” and “DBS Off” stimulation states.

Conclusion: This tablet-based task and analysis protocol correlated strongly with expert clinical assessments of PD motor dysfunction. Additionally, the task showed specificity for PD when compared to ET, another common movement disorder. This specificity was driven by the relative heterogeneity of motor dysfunction of PD compared to ET. Finally, the task was able to distinguish between the “DBS On” and “DBS Off” states within single patients with PD. This task provides temporally-precise and specific information about motor dysfunction in at least two movement disorders that could feasibly correlate to neural activity.

Progressive muscle-strength protocol for the functionality of upper limbs and quality of life in individuals with Parkinson's disease: Pilot study

The effects of physical-therapy intervention on the motor function of upper limbs and the quality of life in patients with Parkinson's disease (PD) are not fully understood. We evaluated the effects of a progressive muscle-strengthening protocol for upper limbs on the functionality and quality of life. Patients were divided into two groups: Intervention (n = 6) and Control (n = 7). Assessment tools used were: Unified Parkinson's Disease Rating Scale (UPDRS), Parkinson's Disease Questionnaire, Nine-Hole Peg Test (9HPT), Test d'Évaluation des Membres Supérieurs de Personnes Âgées (TEMPA), 10-Repetition Maximum (10-RM) and handgrip dynamometer, which were applied pre- and post-intervention, with follow-up for one month after the last training session. Only, the Intervention group (post-intervention) showed significant statistical differences, with the following outcomes: UPDRS III (p = 0.042); 9HPT, right (p = 0.028) and left side (p = 0.028); TEMPA for total right side (p = 0.028), left side (p = 0.028) and total bilateral tasks (p = 0.028); TEMPA task 2 - open a jar and take a spoonful of coffee (p = 0.028), task 3 - pick up a pitcher and pour water into a glass for right (p = 0.046) and left side (p = 0.028), task 5 - write on an envelope and stick on a stamp (p = 0.028), and task 6 - shuffle and deal playing cards (p = 0.028). We observed significant statistical differences between groups (post-intervention) for TEMPA task 6 (p = 0.032), total right side (p = 0.032), and total bilateral tasks (p = 0.032). An increase in the maximum load in the post-intervention stage, based on the 10-RM test, was observed on the right (p = 0.003) and left (p = 0.007) sides. Our results showed an improvement in upper-limb functionality in PD patients submitted to progressive muscle-strength training, although not in quality of life.

Estimation of Parkinson's disease severity using speech features and extreme gradient boosting

In recent years, there is an increasing interest in building e-health systems. The systems built to deliver the health services with the use of internet and communication technologies aim to reduce the costs arising from outpatient visits of patients. Some of the related recent studies propose machine learning-based telediagnosis and telemonitoring systems for Parkinson's disease (PD). Motivated from the studies showing the potential of speech disorders in PD telemonitoring systems, in this study, we aim to estimate the severity of PD from voice recordings of the patients using motor Unified Parkinson's Disease Rating Scale (UPDRS) as the evaluation metric. For this purpose, we apply various speech processing algorithms to the voice signals of the patients and then use these features as input to a two-stage estimation model. The first step is to apply a wrapper-based feature selection algorithm, called Boruta, and select the most informative speech features. The second step is to feed the selected set of features to a decision tree-based boosting algorithm, extreme gradient boosting, which has been recently applied successfully in many machine learning tasks due to its generalization ability and speed. The feature selection analysis showed that the vibration pattern of the vocal fold is an important indicator of PD severity. Besides, we also investigate the effectiveness of using age and years passed since diagnosis as covariates together with speech features. The lowest mean absolute error with 3.87 was obtained by combining these covariates and speech features with prediction level fusion. Graphical Abstract Framework for the proposed UPDRS estimation model.

Rapid motor fluctuations reveal short-timescale neurophysiological biomarkers of Parkinson's disease

Objective.

Identifying neural activity biomarkers of brain disease is essential to provide objective estimates of disease burden, obtain reliable feedback regarding therapeutic efficacy, and potentially to serve as a source of control for closed-loop neuromodulation. In Parkinson’s disease (PD), microelectrode recordings (MER) are routinely performed in the basal ganglia to guide electrode implantation for deep brain stimulation (DBS). While pathologically-excessive oscillatory activity has been observed and linked to PD motor dysfunction broadly, the extent to which these signals provide quantitative information about disease expression and fluctuations, particularly at short timescales, is unknown. Furthermore, the degree to which informative signal features are similar or different across patients has not been rigorously investigated. We sought to determine the extent to which motor error in PD across patients can be decoded on a rapid timescale using spectral features of neural activity.

Approach.

Here, we recorded neural activity from the subthalamic nucleus (STN) of subjects with PD undergoing awake DBS surgery while they performed an objective, continuous behavioral assessment that synthesized heterogenous PD motor manifestations to generate a scalar measure of motor dysfunction at short timescales. We then leveraged natural motor performance variations as a ‘ground truth’ to identify corresponding neurophysiological biomarkers.

Main results.

Support vector machines using multi-spectral decoding of neural signals from the STN succeeded in tracking the degree of motor impairment at short timescales (as short as one second). Spectral power across a wide range of frequencies, beyond the classic ‘β’ oscillations, contributed to this decoding, and multi-spectral models consistently outperformed those generated using more isolated frequency bands. While generalized decoding models derived across subjects were able to estimate motor impairment, patient-specific models typically performed better.

Significance.

These results demonstrate that quantitative information about short-timescale PD motor dysfunction is available in STN neural activity, distributed across various patient-specific spectral components, such that an individualized approach will be critical to fully harness this information for optimal disease tracking and closed-loop neuromodulation.

New Sensor and Wearable Technologies to Aid in the Diagnosis and Treatment Monitoring of Parkinson's Disease

Parkinson's disease (PD) is a degenerative disorder of the brain characterized by the impairment of the nigrostriatal system. This impairment leads to specific motor manifestations (i.e., bradykinesia, tremor, and rigidity) that are assessed through clinical examination, scales, and patient-reported outcomes. New sensor-based and wearable technologies are progressively revolutionizing PD care by objectively measuring these manifestations and improving PD diagnosis and treatment monitoring. However, their use is still limited in clinical practice, perhaps because of the absence of external validation and standards for their continuous use at home. In the near future, these systems will progressively complement traditional tools and revolutionize the way we diagnose and monitor patients with PD.

Determinants of Dual-Task Training Effect Size in Parkinson Disease: Who Will Benefit Most?

BACKGROUND AND PURPOSE

Dual-task interventions show positive effects in people with Parkinson disease (PD), but it remains unclear which factors determine the size of these benefits. As a secondary analysis of the DUALITY trial, the aim of this study was to assess the determinants of the effect size after 2 types of dual-task practice.

METHODS

We randomly allocated 121 participants with PD to receive either integrated or consecutive dual-task training. Dual-task walking performance was assessed during (i) a backward digit span task (digit), (ii) an auditory Stroop task (Stroop), and (iii) a functional mobile phone task. Baseline descriptive, motor, and cognitive variables were correlated with the change in dual-task gait velocity after the intervention. Factors correlated with the change in dual-task gait velocity postintervention (P < 0.20) were entered into a stepwise forward multiple linear regression model.

RESULTS

Lower dual-task gait velocity and higher cognitive capacity (Scales for Outcomes in Parkinson's Disease-Cognition [ScopaCog]) at baseline were related to larger improvements in dual-task gait velocity after both integrated and consecutive dual-task training for all 3 tasks (β[gait] = -0.45, β[ScopaCog] = 0.34, R = 0.23, P < 0.001, for digit; β[gait] = -0.52, β[ScopaCog] = 0.29, R = 0.26, P < 0.001, for Stroop; and β[gait] = -0.40, β[ScopaCog] = 0.30, R = 0.18, P < 0.001, for mobile phone task).

DISCUSSION AND CONCLUSIONS

Participants with PD who showed a slow dual-task gait velocity and good cognitive functioning at baseline benefited most from the dual-task training, irrespective of the type of training and type of dual-task outcome.Video Abstract available for more insights from the authors (see Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A242).

Application of the Teagar-Kaiser energy operator and wavelet transform for detection of finger tapping contact and release times using accelerometery

The Teager-Kaiser energy operator (TKEO), when applied to a signal gives an estimation of the instantaneous energy of that signal. It, therefore, accentuates both frequency and amplitude changes in a signal. To date, it has been primarily used in communications systems and most popularly in electromyographic signal analysis to detect bursts of muscle activity, however, it has the potential to be used in a number of applications including accelerometer and movement data.A new algorithm was developed which used the TKEO to detect contact times during a finger tapping task from accelerometer data recorded from the index finger. The accuracy of the algorithm was assessed in 7 healthy control subjects during continuous finger tapping across a range of frequencies from 0.5Hz to 2.5Hz. The algorithm proved to be sensitive, correctly identifying at least 99% of all contacts in each of the finger tapping conditions that were tested. The mean absolute error of the contact detection is 14.7 ± 6 ms, while the mean absolute error of the release detection is 36.5 ± 36.3 ms. The proposed algorithm provides a method for the automatic detection of the temporal occurrences of the events of the finger tapping task using only a tri-axial accelerometer. The approach presented provides a means for objective assessment of finger tapping tasks for evaluation of the fine dexterity of the upper limb.

Multilingual Validation of the First French Version of Munich Dysphagia Test-Parkinson's Disease (MDT-PD) in the Luxembourg Parkinson's Study

Introduction: The Munich Dysphagia Test for Parkinson's disease (MDT-PD) was initially developed and validated in the German population as a highly sensitive and specific self-reported screening questionnaire to detect early oropharyngeal symptoms and aspiration risk in patients with idiopathic Parkinson's disease (iPD). In order to make this tool accessible for prevention in the French speaking populations worldwide, we performed the first French translation and provide a linguistic and psychometric validation in the unique multilingual environment of the Luxembourg Parkinson's Study.

Methods: We performed the translation of the MDT-PD into French according to WHO guidelines and subsequently performed the linguistic validation including native speakers. For psychometric validation, 46 patients with parkinsonism from Luxembourg and the Greater Region without severe cognitive impairment were recruited in the frame of the Luxembourg Parkinson's Study. All patients were fluent in French and German completed the MDT-PD in both languages (three times in total).

Results: Linguistic and psychometric validation of the French MDT-PD was reflected by a high test-retest (10/26 questions with K > 0.6 and 10/26 with 0.4 < K ≤ 0.6) and language reliability (12/26 K > 0.6 and 8/26 0.4 < K ≤ 0.6), with an internal consistency for the French (Cronbach's alpha 0.84) and German version (0.87); strong item collinerarity strengthens the internal consistency. No significant differences between MDT-PD score distribution and clinical parameters assessing, for example, disease progression, motor state, or cognition has been observed.

Conclusion: Based on a multilingual approach in the Luxembourg Parkinson Study, we validated the translation of the first French MDT-PD as a non-invasive tool for early detection of dysphagia in patients with parkinsonism. The unexpectedly high number of positively screened patients at earlier disease stages indicate options for new prevention strategies in large French speaking populations worldwide. Diagnostic validation using clinical and endoscopic swallowing evaluation will be continued soon.

Altered Granger causality connectivity within motor-related regions of patients with Parkinson's disease: a resting-state fMRI study

PURPOSE

Although numerous clinical neuroimaging studies have demonstrated that there are functional abnormalities of motor-related regions in patients with Parkinson's disease (PD) by resting-state functional magnetic resonance imaging (fMRI), little studies have explored the causal interactions within these motor-related regions. The present study aimed to examine Granger causality connectivity patterns within motor-related regions in PD patients.

METHODS

Resting-state fMRI was conducted to investigate the causal connectivity differences within motor-related regions between 17 PD patients and 17 matched healthy controls. Subsequently, the relationship between the Unified Parkinson's Disease Rating Scale scores and causal connectivity values within motor-related regions was examined in PD patients.

RESULTS

An increased causal connectivity from the left premotor cortex (PMC) to right primary motor cortex (M1) was found in PD patients compared with that of healthy controls. Also, increased causal flow from the PMC to M1 was negatively correlated with motor scores.

CONCLUSION

PD patients have abnormal causal connectivity in specific motor-related regions, which may reflect a compensatory role of motor deficits in PD patients.

Context-Dependent Behavior in Parkinson’s Disease With Freezing of Gait

Background. Context-dependent behavior is a phenomenon in which people demonstrate superior performance in the context where a motor task was originally learned, but show poorer performance in an unfamiliar context. Previous studies found that people with Parkinson’s disease (PD) demonstrated greater context-dependency than nondisabled adults. Moreover, the frontostriatal circuit appeared to play a role in mediating context-dependent behavior. Neuroimaging studies showed that people with PD and freezing of gait (FoG) had difficulty recruiting the frontostriatal circuit when performing a set-shifting task, known to be mediated by this neural network. Objective. This study aimed to investigate whether individuals with PD and FoG (PD + FoG) would be more context-dependent than those without FoG (PD − FoG). Furthermore, the association between context-dependent behavior and set-shifting ability would be determined. Methods. Sixteen individuals with PD + FoG, 15 participants with PD − FoG, and 15 nondisabled adults (Control) were recruited. The participants practiced 3 numerical sequences, each associated with a specific context. One day following practice, the participants were tested under 2 conditions: the sequence-context associations remained the same as practice or were changed. Set-shifting ability was measured by the Trail Making Test (TMT). Results. Compared to the PD − FoG group, the PD + FoG group showed a greater decrement in normalized motor performance when the sequence-context associations were changed. Context-dependency correlated with the TMT in the PD − FoG group but not in the PD + FoG or Control groups. Conclusion. While people with PD + FoG appeared to be more context-dependent than individuals without FoG, a relationship between context-dependent behavior and set-shifting existed only in those without FoG.

Clinimetric approach to rating scales for the assessment of apathy in Parkinson's disease: A systematic review

A number of rating scales for the assessment of apathy in Parkinson's disease (PD) were developed. Unfortunately, previous studies focused mainly on psychometric criteria rather than on clinimetric principles to develop these assessment instruments. In the clinimetric approach, the clinical validity of a rating scale, rather than its statistical significance, has the priority. The aim of the present systematic review was to capture the clinimetric properties of these rating scales and to identify the measures, which display clinical validity for the assessment of apathy in PD. The systematic search was conducted on Scopus, PsycINFO, PubMed, Web of Science, ScienceDirect, and Medline following the PRISMA guidelines. A total of 44 studies were included and analyzed in this systematic review. The apathy rating scales, which were found to be psychometrically robust and reliable, were actually clinically questionable. The apathy measures, which displayed clinimetric properties, were the Starkstein Apathy Scale (SAS), the 5-item version of the World Health Organization Well-Being Index (WHO-5), the Neurasthenia Scale and the Lille Apathy Rating Scale (LARS). The SAS was found to be clinically valid at a macro-analytic level, particularly when used either to exclude the presence of symptoms of apathy or to evaluate the side effects of medications. The WHO-5 and the Neurasthenia Scale were found to be clinically valid only at a micro-analytic level and can be used as screening measures for the assessment of the severity of symptoms of apathy. The LARS was a clinically valid instrument to be used for the diagnosis of apathy.