Bradykinesia-akinesia incoordination test: validating an online keyboard test of upper limb function

The Motor Dysfunction Seen in Isolated REM Sleep Behavior Disorder

BACKGROUND

Isolated Rapid Eye Movement (REM) sleep Behavior Disorder (iRBD) requires quantitative tools to detect incipient Parkinson's disease (PD).

METHODS

A motor battery was designed and compared with the Movement Disorder Society-Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS-III) in people with iRBD and controls. This included two keyboard-based tests (BRadykinesia Akinesia INcoordination tap test and Distal Finger Tapping) and two dual tasking tests (walking and finger tapping).

RESULTS

We included 33 iRBD patients and 29 controls. The iRBD group performed both keyboard-based tapping tests more slowly (P < 0.001, P = 0.020) and less rhythmically (P < 0.001, P = 0.006) than controls. Unlike controls, the iRBD group increased their walking duration (P < 0.001) and had a smaller amplitude (P = 0.001) and slower (P = 0.007) finger tapping with dual task. The combination of the most salient motor markers showed 90.3% sensitivity for 89.3% specificity (area under the ROC curve [AUC], 0.94), which was higher than the MDS-UPDRS-III (minus action tremor) (69.7% sensitivity, 72.4% specificity; AUC, 0.81) for detecting motor dysfunction.

CONCLUSION

Speed, rhythm, and dual task motor deterioration might be accurate indicators of incipient PD in iRBD. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Estimating presymptomatic episodic memory impairment using simple hand movement tests: A cross-sectional study of a large sample of older adults

INTRODUCTION

Finding low-cost methods to detect early-stage Alzheimer's disease (AD) is a research priority for neuroprotective drug development. Presymptomatic Alzheimer's is associated with gait impairment but hand motor tests, which are more accessible, have hardly been investigated. This study evaluated how home-based Tasmanian (TAS) Test keyboard tapping tests predict episodic memory performance.

METHODS

1169 community participants (65.8 ± 7.4 years old; 73% female) without cognitive symptoms completed online single-key and alternate-key tapping tests and episodic memory, working memory, and executive function cognitive tests.

RESULTS

All single-key (R2 adj  = 8.8%, ΔAIC = 5.2) and alternate-key (R2 adj  = 9.1%, ΔAIC = 8.8) motor features predicted episodic memory performance relative to demographic and mood confounders only (R2 adj  = 8.1%). No tapping features improved estimation of working memory.

DISCUSSION

Brief self-administered online hand movement tests predict asymptomatic episodic memory impairment. This provides a potential low-cost home-based method for stratification of enriched cohorts.

HIGHLIGHTS

We devised two brief online keyboard tapping tests to assess hand motor function. 1169 cognitively asymptomatic adults completed motor- and cognitive tests online. Impaired hand motor function predicted reduced episodic memory performance. This brief self-administered test may aid stratification of community cohorts.

Phenotypic effect of GBA1 variants in individuals with and without Parkinson's disease: The RAPSODI study

BACKGROUND

Variants in the GBA1 gene cause the lysosomal storage disorder Gaucher disease (GD). They are also risk factors for Parkinson's disease (PD), and modify the expression of the PD phenotype. The penetrance of GBA1 variants in PD is incomplete, and the ability to determine who among GBA1 variant carriers are at higher risk of developing PD, would represent an advantage for prognostic and trial design purposes.

OBJECTIVES

To compare the motor and non-motor phenotype of GBA1 carriers and non-carriers.

METHODS

We present the cross-sectional results of the baseline assessment from the RAPSODI study, an online assessment tool for PD patients and GBA1 variant carriers. The assessment includes clinically validated questionnaires, a tap-test, the University of Pennsyllvania Smell Identification Test and cognitive tests. Additional, homogeneous data from the PREDICT-PD cohort were included.

RESULTS

A total of 379 participants completed all parts of the RAPSODI assessment (89 GBA1-negative controls, 169 GBA1-negative PD, 47 GBA1-positive PD, 47 non-affected GBA1 carriers, 27 GD). Eighty-six participants were recruited through PREDICT-PD (43 non-affected GBA1 carriers and 43 GBA1-negative controls). GBA1-positive PD patients showed worse performance in visual cognitive tasks and olfaction compared to GBA1-negative PD patients. No differences were detected between non-affected GBA1 carriers carriers and GBA1-negative controls. No phenotypic differences were observed between any of the non-PD groups.

CONCLUSIONS

Our results support previous evidence that GBA1-positive PD has a specific phenotype with more severe non-motor symptoms. However, we did not reproduce previous findings of more frequent prodromal PD signs in non-affected GBA1 carriers.

Intranasal inorganic cerium oxide nanoparticles ameliorate oxidative stress induced motor manifestations in haloperidol-induced parkinsonism

Cerium oxide nanoparticles (CONPs), owing to their radical scavenging property, have recently emerged as a therapeutic candidate for oxidative stress-mediated neurological diseases. However, oral and intravenous administration of CONPs is limited due to their poor physicochemical characteristics, low bioavailability, rapid systemic clearance, poor blood-brain penetration and dose-dependent toxicity. To overcome these challenges, we developed intranasal CONPs and evaluated their potential in the experimental PD model. CONPs were prepared by homogenous precipitation using tween 80 as a stabilizer and methanol/water as solvent. The optimization was done using Central Composite Design (CCD). The CONPs synthesis was confirmed by UV and FTIR. The optimized CONPs were small-sized (105.1 ± 5.78 nm), spherical (TEM), uniform (PDI, 0.119 ± 0.006) and stable (ZP, -22.7 ± 1.02 mV). Energy-dispersive X-ray analysis showed characteristic signals of Ce in developed CONPs. The X-ray diffraction pattern described the cubic fluorite structure and nano-crystalline nature of CONPs. The CONP anti-oxidant activity was found to be 93.60 ± 0.32% at 25 µg/mL concentration. Finally, motor manifestation studies like the forced swim test, locomotor test, akinesia, catalepsy, and muscle coordination test were conducted to assess the motor dysfunctions and behavioral activity in all four animal groups. Results of the in vivo motor manifestation studies in the haloperidol-induced PD rat model showed that co-administration of intranasal CONPs along with a half dose of levodopa resulted in significant protection, and results were significantly different from the untreated group but not significantly different from the healthy group. In conclusion, intranasal CONPs can be useful in ameliorating oxidative stress through their antioxidant effect and could be prospective therapeutics for the treatment of motor manifestations in Parkinson's disease.

Parkinson Disease Recognition Using a Gamified Website: Machine Learning Development and Usability Study

BACKGROUND

Parkinson disease (PD) affects millions globally, causing motor function impairments. Early detection is vital, and diverse data sources aid diagnosis. We focus on lower arm movements during keyboard and trackpad or touchscreen interactions, which serve as reliable indicators of PD. Previous works explore keyboard tapping and unstructured device monitoring; we attempt to further these works with structured tests taking into account 2D hand movement in addition to finger tapping. Our feasibility study uses keystroke and mouse movement data from a remotely conducted, structured, web-based test combined with self-reported PD status to create a predictive model for detecting the presence of PD.

OBJECTIVE

Analysis of finger tapping speed and accuracy through keyboard input and analysis of 2D hand movement through mouse input allowed differentiation between participants with and without PD. This comparative analysis enables us to establish clear distinctions between the two groups and explore the feasibility of using motor behavior to predict the presence of the disease.

METHODS

Participants were recruited via email by the Hawaii Parkinson Association (HPA) and directed to a web application for the tests. The 2023 HPA symposium was also used as a forum to recruit participants and spread information about our study. The application recorded participant demographics, including age, gender, and race, as well as PD status. We conducted a series of tests to assess finger tapping, using on-screen prompts to request key presses of constant and random keys. Response times, accuracy, and unintended movements resulting in accidental presses were recorded. Participants performed a hand movement test consisting of tracing straight and curved on-screen ribbons using a trackpad or mouse, allowing us to evaluate stability and precision of 2D hand movement. From this tracing, the test collected and stored insights concerning lower arm motor movement.

RESULTS

Our formative study included 31 participants, 18 without PD and 13 with PD, and analyzed their lower limb movement data collected from keyboards and computer mice. From the data set, we extracted 28 features and evaluated their significances using an extra tree classifier predictor. A random forest model was trained using the 6 most important features identified by the predictor. These selected features provided insights into precision and movement speed derived from keyboard tapping and mouse tracing tests. This final model achieved an average F1-score of 0.7311 (SD 0.1663) and an average accuracy of 0.7429 (SD 0.1400) over 20 runs for predicting the presence of PD.

CONCLUSIONS

This preliminary feasibility study suggests the possibility of using technology-based limb movement data to predict the presence of PD, demonstrating the practicality of implementing this approach in a cost-effective and accessible manner. In addition, this study demonstrates that structured mouse movement tests can be used in combination with finger tapping to detect PD.

The Emergence and Progression of Motor Dysfunction in Individuals at Risk of Parkinson's Disease

BACKGROUND

PREDICT-PD is a United Kingdom population-based study aiming to stratify individuals for future Parkinson's disease (PD) using a risk algorithm.

METHODS

A randomly selected, representative sample of participants in PREDICT-PD were examined using several motor assessments, including the motor section of the Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS)-III, at baseline (2012) and after an average of 6 years of follow-up. We checked for new PD diagnoses in participants seen at baseline and examined the association between risk scores and incident sub-threshold parkinsonism, motor decline (increasing ≥5 points in MDS-UPDRS-III) and single motor domains in the MDS-UPDRS-III. We replicated analyses in two independent datasets (Bruneck and Parkinson's Progression Markers Initiative [PPMI]).

RESULTS

After 6 years of follow-up, the PREDICT-PD higher-risk group (n = 33) had a greater motor decline compared with the lower-risk group (n = 95) (30% vs. 12.5%, P = 0.031). Two participants (both considered higher risk at baseline) were given a diagnosis of PD during follow-up, with motor signs emerging between 2 and 5 years before diagnosis. A meta-analysis of data from PREDICT-PD, Bruneck, and PPMI showed an association between PD risk estimates and incident sub-threshold parkinsonism (odds ratio [OR], 2.01 [95% confidence interval (CI), 1.55-2.61]), as well as new onset bradykinesia (OR, 1.69 [95% CI, 1.33-2.16]) and action tremor (OR, 1.61 [95% CI, 1.30-1.98]).

CONCLUSIONS

Risk estimates using the PREDICT-PD algorithm were associated with the occurrence of sub-threshold parkinsonism, including bradykinesia and action tremor. The algorithm could also identify individuals whose motor examination experience a decline over time. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

A smartphone-based tapping task as a marker of medication response in Parkinson's disease: a proof of concept study

Tapping tasks have the potential to distinguish between ON-OFF fluctuations in Parkinson's disease (PD) possibly aiding assessment of medication status in e-diaries and research. This proof of concept study aims to assess the feasibility and accuracy of a smartphone-based tapping task (developed as part of the cloudUPDRS-project) to discriminate between ON-OFF used in the home setting without supervision. 32 PD patients performed the task before their first medication intake, followed by two test sessions after 1 and 3 h. Testing was repeated for 7 days. Index finger tapping between two targets was performed as fast as possible with each hand. Self-reported ON-OFF status was also indicated. Reminders were sent for testing and medication intake. We studied task compliance, objective performance (frequency and inter-tap distance), classification accuracy and repeatability of tapping. Average compliance was 97.0% (± 3.3%), but 16 patients (50%) needed remote assistance. Self-reported ON-OFF scores and objective tapping were worse pre versus post medication intake (p < 0.0005). Repeated tests showed good to excellent test-retest reliability in ON (0.707 ≤ ICC ≤ 0.975). Although 7 days learning effects were apparent, ON-OFF differences remained. Discriminative accuracy for ON-OFF was particularly good for right-hand tapping (0.72 ≤ AUC ≤ 0.80). Medication dose was associated with ON-OFF tapping changes. Unsupervised tapping tests performed on a smartphone have the potential to classify ON-OFF fluctuations in the home setting, despite some learning and time effects. Replication of these results are needed in a wider sample of patients.

Outcome Measures for Disease-Modifying Trials in Parkinson's Disease: Consensus Paper by the EJS ACT-PD Multi-Arm Multi-Stage Trial Initiative

BACKGROUND

Multi-arm, multi-stage (MAMS) platform trials can accelerate the identification of disease-modifying treatments for Parkinson's disease (PD) but there is no current consensus on the optimal outcome measures (OM) for this approach.

OBJECTIVE

To provide an up-to-date inventory of OM for disease-modifying PD trials, and a framework for future selection of OM for such trials.

METHODS

As part of the Edmond J Safra Accelerating Clinical Trials in Parkinson Disease (EJS ACT-PD) initiative, an expert group with Patient and Public Involvement and Engagement (PPIE) representatives' input reviewed and evaluated available evidence on OM for potential use in trials to delay progression of PD. Each OM was ranked based on aspects such as validity, sensitivity to change, participant burden and practicality for a multi-site trial. Review of evidence and expert opinion led to the present inventory.

RESULTS

An extensive inventory of OM was created, divided into: general, motor and non-motor scales, diaries and fluctuation questionnaires, cognitive, disability and health-related quality of life, capability, quantitative motor, wearable and digital, combined, resource use, imaging and wet biomarkers, and milestone-based. A framework for evaluation of OM is presented to update the inventory in the future. PPIE input highlighted the need for OM which reflect their experience of disease progression and are applicable to diverse populations and disease stages.

CONCLUSION

We present a range of OM, classified according to a transparent framework, to aid selection of OM for disease-modifying PD trials, whilst allowing for inclusion or re-classification of relevant OM as new evidence emerges.

Clinical Motor Coordination Tests in Adult Neurology: A Scoping Review

Purpose: This scoping review aimed to identify which clinical tests are used to assess upper limb, lower limb, and trunk motor coordination, and their metric and measurement properties for adult neurological populations. Method: MEDLINE (1946-) and EMBASE (1996-) databases were searched using keywords such as movement quality, motor performance, motor coordination, assessment, and psychometrics. Data regarding the body part assessed, neurological condition, psychometric properties, and scored metrics of spatial and/or temporal coordination were independently extracted by two reviewers. Alternate versions of some tests such as the Finger-to-Nose Test were included. Results: Fifty-one included articles yielded 2 tests measuring spatial coordination, 7 tests measuring temporal coordination, and 10 tests measuring both. Scoring metrics and measurement properties differed between tests, with a majority of tests having good-to-excellent measurement properties. Conclusions: The metrics of motor coordination scored by current tests vary. Since tests do not assess functional task performance, the onus falls on clinicians to infer the connection between coordination impairments and functional deficits. Clinical practice would benefit from the development of a battery of tests that assesses the metrics of coordination related to functional performance.

Challenges of Incorporating Digital Health Technology Outcomes in a Clinical Trial: Experiences from PD STAT

Digital health technologies (DHTs) have great potential for use as clinical trial outcomes; however, practical issues need to be addressed in order to maximise their benefit. We describe our experience of incorporating two DHTs as secondary/exploratory outcome measures in PD STAT, a randomised clinical trial of simvastatin in people with Parkinson's disease. We found much higher rates of missing data in the DHTs than the traditional outcome measures, in particular due to technical and software difficulties. We discuss methods to address these obstacles in terms of protocol design, workforce training and data management.

Remote Assessments of Hand Function in Neurological Disorders: Systematic Review

BACKGROUND

Loss of fine motor skills is observed in many neurological diseases, and remote monitoring assessments can aid in early diagnosis and intervention. Hand function can be regularly assessed to monitor loss of fine motor skills in people with central nervous system disorders; however, there are challenges to in-clinic assessments. Remotely assessing hand function could facilitate monitoring and supporting of early diagnosis and intervention when warranted.

OBJECTIVE

Remote assessments can facilitate the tracking of limitations, aiding in early diagnosis and intervention. This study aims to systematically review existing evidence regarding the remote assessment of hand function in populations with chronic neurological dysfunction.

METHODS

PubMed and MEDLINE, CINAHL, Web of Science, and Embase were searched for studies that reported remote assessment of hand function (ie, outside of traditional in-person clinical settings) in adults with chronic central nervous system disorders. We excluded studies that included participants with orthopedic upper limb dysfunction or used tools for intervention and treatment. We extracted data on the evaluated hand function domains, validity and reliability, feasibility, and stage of development.

RESULTS

In total, 74 studies met the inclusion criteria for Parkinson disease (n=57, 77% studies), stroke (n=9, 12%), multiple sclerosis (n=6, 8%), spinal cord injury (n=1, 1%), and amyotrophic lateral sclerosis (n=1, 1%). Three assessment modalities were identified: external device (eg, wrist-worn accelerometer), smartphone or tablet, and telerehabilitation. The feasibility and overall participant acceptability were high. The most common hand function domains assessed included finger tapping speed (fine motor control and rigidity), hand tremor (pharmacological and rehabilitation efficacy), and finger dexterity (manipulation of small objects required for daily tasks) and handwriting (coordination). Although validity and reliability data were heterogeneous across studies, statistically significant correlations with traditional in-clinic metrics were most commonly reported for telerehabilitation and smartphone or tablet apps. The most readily implementable assessments were smartphone or tablet-based.

CONCLUSIONS

The findings show that remote assessment of hand function is feasible in neurological disorders. Although varied, the assessments allow clinicians to objectively record performance in multiple hand function domains, improving the reliability of traditional in-clinic assessments. Remote assessments, particularly via telerehabilitation and smartphone- or tablet-based apps that align with in-clinic metrics, facilitate clinic to home transitions, have few barriers to implementation, and prompt remote identification and treatment of hand function impairments.

The potential utility of smell testing to screen for neurodegenerative disorders

INTRODUCTION

Loss of smell is a common early feature of neurodegenerative diseases including Alzheimer's and Parkinson's disease. Identifying these conditions in their early stages is important to understand more about early pathophysiological events and the development of disease modifying therapies. Smell testing may be an effective future tool for screening large populations for early neurodegeneration.

AREAS COVERED

: In this review, we appraise the evidence for, and discuss the likelihood of, the use of smell testing in large screening programs to detect early neurodegeneration. We evaluate the predictive power of smell tests for neurodegenerative disease, compare performance to other established screening programs, and discuss ethical and practical considerations and limitations.

EXPERT OPINION

: Even if disease modifying therapies were available for neurodegenerative disease, smell tests alone are unlikely to have high enough predictive power to be used in a future screening program. However, we believe they could be a valuable component of a short battery of tests or part of a stepwise process that together could more accurately identify early neurodegeneration in large populations.

Developing and assessing a new web-based tapping test for measuring distal movement in Parkinson's disease: a Distal Finger Tapping test

Disability in Parkinson's disease (PD) is measured by standardised scales including the MDS-UPDRS, which are subject to high inter and intra-rater variability and fail to capture subtle motor impairment. The BRadykinesia Akinesia INcoordination (BRAIN) test is a validated keyboard tapping test, evaluating proximal upper-limb motor impairment. Here, a new Distal Finger Tapping (DFT) test was developed to assess distal upper-limb function. Kinetic parameters of the test include kinesia score (KS20, key taps over 20 s), akinesia time (AT20, mean dwell-time on each key) and incoordination score (IS20, variance of travelling time between key taps). To develop and evaluate a new keyboard-tapping test for objective and remote distal motor function in PD patients. The DFT and BRAIN tests were assessed in 55 PD patients and 65 controls. Test scores were compared between groups and correlated with the MDS-UPDRS-III finger tapping sub-scores. Nine additional PD patients were recruited for monitoring motor fluctuations. All three parameters discriminated effectively between PD patients and controls, with KS20 performing best, yielding 79% sensitivity for 85% specificity; area under the receiver operating characteristic curve (AUC) = 0.90. A combination of DFT and BRAIN tests improved discrimination (AUC = 0.95). Among three parameters, KS20 showed a moderate correlation with the MDS-UPDRS finger-tapping sub-score (Pearson's r = - 0.40, p = 0.002). Further, the DFT test detected subtle changes in motor fluctuation states which were not reflected clearly by the MDS-UPDRS-III finger tapping sub-scores. The DFT test is an online tool for assessing distal movements in PD, with future scope for longitudinal monitoring of motor complications.

Association of HLA-DRB1, DQA1 and DQB1 alleles and haplotype in Parkinson's disease from South India

Parkinson's disease (PD) is a chronic, neurodegenerative motor disease exhibiting familial and sporadic forms. The present study was aimed to elucidate the association of HLA-DRB1*, DQA1* and DQB1* alleles with PD. A total of 105 PD patients and 100 healthy controls were typed by PCR-SSP method. We further carried out high-resolution genotyping for DQB1 and DQA1. Results revealed the increased frequencies of alleles DRB1*04 (OR = 2.36), DRB1* 13 (OR = 4.04), DQA1* 01:04:01 (OR = 4.51), DQB1*02:01 (OR = 2.66) and DQB1*06:03 (OR = 2.65) in PD patients suggesting susceptible associations. Further, decreased frequencies observed for alleles DRB1*10 (OR = 0.34), DRB1*15 (OR = 0.44), DQA1*04:01 (OR = 0.28), DQA1*06:01 (OR = 0.11) and HLA-DQB1*05:01 (OR = 0.37) among patients have suggested protective associations. Significant disease associations were observed for two-locus haplotype such as DRB1*13-DQB1*06:03 (OR = 11.52), DQA1*01:041-DQB1*06:03 (OR = 16.50), DQA1*01:041-DQB1*05:02 (OR = 5.38) and DQA1*04:01-DQB1*06:03 (OR = 3.027). Protective associations were observed for haplotypes DRB1*10-DQB1*05:01 (OR = 0.21), DRB1*15-DQB1*06 (OR = 0.006), DQA1*04:01-DQB1*05:01 (OR = 0.400) and DQA1*04:01-DQB1*05:03 (OR = 0.196). The critical amino acid residue analyses have revealed strong susceptible association for the residues of DQB1 alleles such as: L²⁶, S²⁸, K⁷¹, T⁷¹ and A⁷⁴, Y⁹, S³⁰, D³⁷, I³⁷, A³⁸, A⁵⁷ and S⁵⁷; and for the residues of DQA1 alleles such as: C¹¹, F⁶¹, I⁷⁴, and M⁷⁶. Similarly, amino acid residues such as A¹³, G²⁶, Y²⁶, A⁷¹, S⁷⁴, L⁹ and V³⁸ of HLA-DQB1 alleles and residues such as Y¹¹, G⁶¹, S⁷⁴ and L⁷⁶ of DQA1 alleles showed protective associations. Thus, our study documented the susceptible and protective associations of DRB1*, DQB1 and DQA1 alleles and haplotypes in developing the disease and their influence on longevity of PD patients in south India.

Optimising classification of Parkinson's disease based on motor, olfactory, neuropsychiatric and sleep features

Olfactory loss, motor impairment, anxiety/depression, and REM-sleep behaviour disorder (RBD) are prodromal Parkinson’s disease (PD) features. PD risk prediction models typically dichotomize test results and apply likelihood ratios (LRs) to scores above and below cut-offs. We investigate whether LRs for specific test values could enhance classification between PD and controls. PD patient data on smell (UPSIT), possible RBD (RBD Screening Questionnaire), and anxiety/depression (LADS) were taken from the Tracking Parkinson’s study (n = 1046). For motor impairment (BRAIN test) in PD cases, published data were supplemented (n = 87). Control data (HADS for anxiety/depression) were taken from the PREDICT-PD pilot study (n = 1314). UPSIT, RBDSQ, and anxiety/depression data were analysed using logistic regression to determine which items were associated with PD. Gaussian distributions were fitted to BRAIN test scores. LRs were calculated from logistic regression models or score distributions. False-positive rates (FPRs) for specified detection rates (DRs) were calculated. Sixteen odours were associated with PD; LRs for this set ranged from 0.005 to 5511. Six RBDSQ and seven anxiety/depression questions were associated with PD; LRs ranged from 0.35 to 69 and from 0.002 to 402, respectively. BRAIN test LRs ranged from 0.16 to 1311. For a 70% DR, the FPR was 2.4% for the 16 odours, 4.6% for anxiety/depression, 16.0% for the BRAIN test, and 20.0% for the RBDSQ. Specific selections of (prodromal) PD marker features rather than dichotomized marker test results optimize PD classification. Such optimized classification models could improve the ability of algorithms to detect prodromal PD; however, prospective studies are needed to investigate their value for PD-prediction models.

Slow Motion Analysis of Repetitive Tapping (SMART) Test: Measuring Bradykinesia in Recently Diagnosed Parkinson's Disease and Idiopathic Anosmia

BACKGROUND

Bradykinesia is the defining motor feature of Parkinson's disease (PD). There are limitations to its assessment using standard clinical rating scales, especially in the early stages of PD when a floor effect may be observed.

OBJECTIVE

To develop a quantitative method to track repetitive tapping movements and to compare people in the early stages of PD, healthy controls, and individuals with idiopathic anosmia.

METHODS

This was a cross-sectional study of 99 participants (early-stage PD = 26, controls = 64, idiopathic anosmia = 9). For each participant, repetitive finger tapping was recorded over 20 seconds using a smartphone at 240 frames per second. From each video, amplitude between fingers, frequency (number of taps per second), and velocity (distance travelled per second) was extracted. Clinical assessment was based on the motor section of the MDS-UPDRS.

RESULTS

People in the early stage of PD performed the task with slower velocity (p <  0.001) and with greater frequency slope than controls (p = 0.003). The combination of reduced velocity and greater frequency slope obtained the best accuracy to separate early-stage PD from controls based on metric thresholds alone (AUC = 0.88). Individuals with anosmia exhibited slower velocity (p = 0.001) and smaller amplitude (p <  0.001) compared with controls.

CONCLUSION

We present a simple, proof-of-concept method to detect early motor dysfunction in PD. Mean tap velocity appeared to be the best parameter to differentiate patients with PD from controls. Patients with anosmia also showed detectable differences in motor performance compared with controls which may suggest that some were in the prodromal phase of PD.

The SleepFit Tablet Application for Home-Based Clinical Data Collection in Parkinson Disease: User-Centric Development and Usability Study

BACKGROUND

Parkinson disease (PD) is a common, multifaceted neurodegenerative disorder profoundly impacting patients' autonomy and quality of life. Assessment in real-life conditions of subjective symptoms and objective metrics of mobility and nonmotor symptoms such as sleep disturbance is strongly advocated. This information would critically guide the adaptation of antiparkinsonian medications and nonpharmacological interventions. Moreover, since the spread of the COVID-19 pandemic, health care practices are being reshaped toward a more home-based care. New technologies could play a pivotal role in this new approach to clinical care. Nevertheless, devices and information technology tools might be unhandy for PD patients, thus dramatically limiting their widespread employment.

OBJECTIVE

The goals of the research were development and usability evaluation of an application, SleepFit, for ecological momentary assessment of objective and subjective clinical metrics at PD patients' homes, and as a remote tool for researchers to monitor patients and integrate and manage data.

METHODS

An iterative and user-centric strategy was employed for the development of SleepFit. The core structure of SleepFit consists of (1) an electronic finger-tapping test; (2) motor, sleepiness, and emotional subjective scales; and (3) a sleep diary. Applicable design, ergonomic, and navigation principles have been applied while tailoring the application to the specific patient population. Three progressively enhanced versions of the application (alpha, v1.0, v2.0) were tested by a total of 56 patients with PD who were asked to perform multiple home assessments 4 times per day for 2 weeks. Patient compliance was calculated as the proportion of completed tasks out of the total number of expected tasks. Satisfaction on the latest version (v2.0) was evaluated as potential willingness to use SleepFit again after the end of the study.

RESULTS

From alpha to v1.0, SleepFit was improved in graphics, ergonomics, and navigation, with automated flows guiding the patients in performing tasks throughout the 24 hours, and real-time data collection and consultation were made possible thanks to a remote web portal. In v2.0, the kiosk-mode feature restricts the use of the tablet to the SleepFit application only, thus preventing users from accidentally exiting the application. A total of 52 (4 dropouts) patients were included in the analyses. Overall compliance (all versions) was 88.89% (5707/6420). SleepFit was progressively enhanced and compliance increased from 87.86% (2070/2356) to 89.92% (2899/3224; P=.04). Among the patients who used v2.0, 96% (25/26) declared they would use SleepFit again.

CONCLUSIONS

SleepFit can be considered a state-of-the-art home-based system that increases compliance in PD patients, ensures high-quality data collection, and works as a handy tool for remote monitoring and data management in clinical research. Thanks to its user-friendliness and modular structure, it could be employed in other clinical studies with minimum adaptation efforts.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02723396; https://clinicaltrials.gov/ct2/show/NCT02723396.

Improving estimation of Parkinson's disease risk-the enhanced PREDICT-PD algorithm

We previously reported a basic algorithm to identify the risk of Parkinson’s disease (PD) using published data on risk factors and prodromal features. Using this algorithm, the PREDICT-PD study identified individuals at increased risk of PD and used tapping speed, hyposmia and REM sleep behaviour disorder (RBD) as “intermediate” markers of prodromal PD in the absence of sufficient incident cases. We have now developed and tested an enhanced algorithm which incorporates the intermediate markers into the risk model. Risk estimates were compared using the enhanced and the basic algorithm in members of the PREDICT-PD pilot cohort. The enhanced PREDICT-PD algorithm yielded a much greater range of risk estimates than the basic algorithm (93–609-fold difference between the 10th and 90th centiles vs 10–13-fold respectively). There was a greater increase in the risk of PD with increasing risk scores for the enhanced algorithm than for the basic algorithm (hazard ratios per one standard deviation increase in log risk of 2.75 [95% CI 1.68–4.50; p < 0.001] versus 1.47 [95% CI 0.86–2.51; p = 0.16] respectively). Estimates from the enhanced algorithm also correlated more closely with subclinical striatal DaT-SPECT dopamine depletion (R² = 0.164, p = 0.005 vs R² = 0.043, p = 0.17). Incorporating the previous intermediate markers of prodromal PD and using likelihood ratios improved the accuracy of the PREDICT-PD prediction algorithm.

Evaluation of upper limb function with digitizing tablet-based tests: reliability and discriminative validity in healthy persons and patients with neurological disorders

PURPOSE

To evaluate discriminative validity, relative reliability and absolute reliability of four tablet-based tests for the evaluation of upper limb motor function in healthy persons and patients with neurological disorders.

METHODS

Cross-sectional study in 54 participants: 29 patients with upper limb movement impairment due to a neurological condition recruited from an inpatient rehabilitation centre and 25 healthy persons. Accuracy, speed and path length were analysed for four tablet-based tests: "Spiral drawings," "Tapping," "Follow the dot" and "Trace a star." The area under the receiver operating characteristic curve (AUC) was used to evaluate discriminative validity. Relative reliability was analysed with the intra-class correlation coefficient (ICC), and absolute reliability by limits of agreement (LoA) and minimal detectable difference (MDD).

RESULTS

All four tests showed excellent discriminative validity for the parameter accuracy (AUC 0.93-0.98). Tapping was the best test for discriminating patients from healthy persons. Test-retest reliability was good for accuracy in all tests (ICC = 0.76-0.88), but poor to moderate for speed and path length (ICC = 0.20-0.69). The MDD varied between 14% and 38%. Performance on the four tablet-based tests was stable between sessions, indicating that there was no learning effect.

CONCLUSION

The parameter accuracy showed excellent discriminative validity and reliability in all four tablet-based tests. Discriminative validity was excellent for all three parameters in the Tapping test. In the other tasks speed showed good to poor reliability, while the reliability of path-length was poor in all tasks. Results were comparable for the dominant and non-dominant hand. Tablet-based tests have the advantage that patients can use them for self-monitoring of upper limb motor function.Implications for rehabilitationFour tablet-based tests for the assessment of upper limb motor function in patients with upper limb neurological dysfunction were evaluated: "Spiral drawings", "Tapping", "Follow the dot" and "Trace a star". The parameter accuracy in these four tests had excellent discriminative validity and good reliability.Patients can perform the tests independently at home for self-monitoring of progress. This may increase patients' motivation to exercise at home.The results can be sent to physicians, enabling the earlier detection of deterioration, which may require medical attention.

The BRadykinesia Akinesia INcoordination (BRAIN) Tap Test: Capturing the Sequence Effect

BACKGROUND

The BRadykinesia Akinesia INcoordination (BRAIN) tap test is an online keyboard tapping task that has been previously validated to assess upper limb motor function in Parkinson's disease (PD).

OBJECTIVES

To develop a new parameter that detects a sequence effect and to reliably distinguish between PD patients on and off medication. In addition, we sought to validate a mobile version of the test for use on smartphones and tablet devices.

METHODS

The BRAIN test scores in 61 patients with PD and 93 healthy controls were compared. A range of established parameters captured number and accuracy of alternate taps. The new velocity score recorded the intertap speed. Decrement in the velocity score was used as a marker for the sequence effect. In the validation phase, 19 PD patients and 19 controls were tested using different hardware including mobile devices.

RESULTS

Quantified slopes from the velocity score demonstrated bradykinesia (sequence effect) in PD patients (slope cut-off -0.002) with 58% sensitivity and 81% specificity (discovery phase of the study) and 65% sensitivity and 88% specificity (validation phase). All BRAIN test parameters differentiated between on and off medication states in PD. Differentiation between PD patients and controls was possible on all hardware versions of the test.

CONCLUSION

The BRAIN tap test is a simple, user-friendly, and free-to-use tool for the assessment of upper limb motor dysfunction in PD, which now includes a measure of bradykinesia.

Remote Monitoring of Treatment Response in Parkinson's Disease: The Habit of Typing on a Computer

OBJECTIVE

The recent advances in technology are opening a new opportunity to remotely evaluate motor features in people with Parkinson's disease (PD). We hypothesized that typing on an electronic device, a habitual behavior facilitated by the nigrostriatal dopaminergic pathway, could allow for objectively and nonobtrusively monitoring parkinsonian features and response to medication in an at-home setting.

METHODS

We enrolled 31 participants recently diagnosed with PD who were due to start dopaminergic treatment and 30 age-matched controls. We remotely monitored their typing pattern during a 6-month (24 weeks) follow-up period before and while dopaminergic medications were being titrated. The typing data were used to develop a novel algorithm based on recursive neural networks and detect participants' responses to medication. The latter were defined by the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) minimal clinically important difference. Furthermore, we tested the accuracy of the algorithm to predict the final response to medication as early as 21 weeks prior to the final 6-month clinical outcome.

RESULTS

The score on the novel algorithm based on recursive neural networks had an overall moderate kappa agreement and fair area under the receiver operating characteristic (ROC) curve with the time-coincident UPDRS-III minimal clinically important difference. The participants classified as responders at the final visit (based on the UPDRS-III minimal clinically important difference) had higher scores on the novel algorithm based on recursive neural networks when compared with the participants with stable UPDRS-III, from the third week of the study onward.

CONCLUSIONS

This preliminary study suggests that remotely gathered unsupervised typing data allows for the accurate detection and prediction of drug response in PD. © 2019 International Parkinson and Movement Disorder Society.

Reduced habit-driven errors in Parkinson's Disease

Parkinson’s Disease can be understood as a disorder of motor habits. A prediction of this theory is that early stage Parkinson’s patients will display fewer errors caused by interference from previously over-learned behaviours. We test this prediction in the domain of skilled typing, where actions are easy to record and errors easy to identify. We describe a method for categorizing errors as simple motor errors or habit-driven errors. We test Spanish and English participants with and without Parkinson’s, and show that indeed patients make fewer habit errors than healthy controls, and, further, that classification of error type increases the accuracy of discriminating between patients and healthy controls. As well as being a validation of a theory-led prediction, these results offer promise for automated, enhanced and early diagnosis of Parkinson’s Disease.

Study protocol for a randomised pilot study of a computer-based, non-pharmacological cognitive intervention for motor slowing and motor fatigue in Parkinson's disease

Background

Parkinson’s disease (PD) is a chronic, neurodegenerative disorder affecting over 137,000 people in the UK and an estimated five million people worldwide. Treatment typically involves long-term dopaminergic therapy, which improves motor symptoms, but is associated with dose-limiting side effects. Developing effective complementary, non-pharmacological interventions is of considerable importance. This paper presents the protocol for a three-arm pilot study to test the implementation of computer-based cognitive training that aims to produce improvements or maintenance of motor slower and motor fatigue symptoms in people with PD. The primary objective is to assess recruitment success and usability of external data capture devices during the intervention. The secondary objectives are to obtain estimates of variance and effect size for changes in primary and secondary outcome measures to inform sample size calculations and study design for a larger scale trial.

Methods

The study aims to recruit between 40 and 60 adults with early- to middle-stage PD (Hoehn and Yahr 1–3) from National Health Service (NHS) outpatients’ clinics and support groups across North Wales, UK. Participants will be randomised to receive training over five sessions in either a spatial grid navigation task, a sequential subtraction task or a spatial memory task. Patient-centred outcome measures will include motor examination scores from part 3 of the UPDRS-III and data from movement kinematic and finger tapping tasks.

Discussion

The results of this study will provide information regarding the feasibility of conducting a larger randomised control trial of non-pharmacological cognitive interventions of motor symptoms in PD.

Trial registration

ISRCTN, ISRCTN12565492. Registered 4 April 2018—retrospectively registered, in accordance with the WHO Trial Registration Data Set.

Electronic supplementary material

The online version of this article (10.1186/s40814-018-0375-4) contains supplementary material, which is available to authorized users.

An early diagnosis is not the same as a timely diagnosis of Parkinson's disease

Parkinson’s disease is a common neurodegenerative condition that has significant costs to the individual patient and to society. The pathology starts up to a decade before symptoms are severe enough to allow a diagnosis using current criteria. Although the search for disease-modifying treatment continues, it is vital to understand what the right time is for diagnosis. Diagnosis of Parkinson’s disease is based on the classic clinical criteria, but the presence of other clinical features and disease biomarkers may allow earlier diagnosis, at least in a research setting. In this review, we identify the benefits of an early diagnosis, including before the classic clinical features occur. However, picking the right point for a “timely” diagnosis will vary depending on the preferences of the individual patient, efficacy (or existence) of disease-modifying treatment, and the ability for health systems to provide support and management for individuals at every stage of the disease. Good evidence for the quality-of-life benefits of existing symptomatic treatment supports the argument for earlier diagnosis at a time when symptoms are already present. This argument would be significantly bolstered by the development of disease-modifying treatments. Benefits of early diagnosis and treatment would affect not only the individual (and their families) but also the wider society and the research community. Ultimately, however, shared decision-making and the principles of autonomy, beneficence, and non-maleficence will need to be applied on an individual basis when considering a “timely” diagnosis.

Is Exenatide a Treatment for Parkinson's Disease?

There is growing interest in the use of glucagon-like peptide-1 agonists as treatments for Parkinson's disease following the recent publication of the results of the Exenatide-PD trial. In this randomized, double-blind, placebo controlled trial, patients with moderate stage Parkinson's disease treated with once-weekly subcutaneous injections of exenatide 2 mg (Bydureon) for 48 weeks, had a 3.5-point advantage over the placebo group in the Movement Disorders Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) motor subscale (Part 3) in the practically defined OFF medication state, 12 weeks after cessation of the trial drug. In this article, we discuss some of the important issues of relevance to this trial, with regards to trial design, patient selection, choice of outcome measure and also place into context the implications these results have for patients with Parkinson's disease and the wider research community.

Assessing cognitive dysfunction in Parkinson's disease: An online tool to detect visuo-perceptual deficits

BACKGROUND

People with Parkinson's disease (PD) who develop visuo-perceptual deficits are at higher risk of dementia, but we lack tests that detect subtle visuo-perceptual deficits and can be performed by untrained personnel. Hallucinations are associated with cognitive impairment and typically involve perception of complex objects. Changes in object perception may therefore be a sensitive marker of visuo-perceptual deficits in PD.

OBJECTIVE

We developed an online platform to test visuo-perceptual function. We hypothesised that (1) visuo-perceptual deficits in PD could be detected using online tests, (2) object perception would be preferentially affected, and (3) these deficits would be caused by changes in perception rather than response bias.

METHODS

We assessed 91 people with PD and 275 controls. Performance was compared using classical frequentist statistics. We then fitted a hierarchical Bayesian signal detection theory model to a subset of tasks.

RESULTS

People with PD were worse than controls at object recognition, showing no deficits in other visuo-perceptual tests. Specifically, they were worse at identifying skewed images (P < .0001); at detecting hidden objects (P = .0039); at identifying objects in peripheral vision (P < .0001); and at detecting biological motion (P = .0065). In contrast, people with PD were not worse at mental rotation or subjective size perception. Using signal detection modelling, we found this effect was driven by change in perceptual sensitivity rather than response bias.

CONCLUSIONS

Online tests can detect visuo-perceptual deficits in people with PD, with object recognition particularly affected. Ultimately, visuo-perceptual tests may be developed to identify at-risk patients for clinical trials to slow PD dementia. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

The BRAIN test: a keyboard-tapping test to assess disability and clinical features of multiple sclerosis

Background

The BRadykinesia Akinesia INcordination (BRAIN) test is an online keyboard-tapping test previously validated as a sensitive tool for detecting signs of Parkinson’s disease.

Objectives

To determine whether the BRAIN test can measure disability in MS and identify the presence of pyramidal or cerebellar dysfunction.

Methods

Kinesia scores (KS, number of key taps in 30 s), akinesia times (AT, mean dwell time on each key) and incoordination scores (IS, variance of travelling time between keys) were calculated in 39 MS patients. These were correlated against the Expanded Disability Status Scale (EDSS) scores, pyramidal and cerebellar functional system scores and 9-hole peg test scores.

Results

EDSS correlated with KS (r = − 0.594, p < 0.001), AT (r = 0.464, p = 0.003) and IS (r = 0.423, p = 0.007). 9-HPT scores strongly correlated with KS (r = 0.926, p < 0.001). Pyramidal scores correlated with KS (r = − 0.517, p < 0.001). Cerebellar scores correlated with KS (r = − 0.665, p < 0.001), AT (r = 0.567, p < 0.001) and IS (r = 0.546, p = 0.007). Receiver operating characteristic curves demonstrate that KS can distinguish between the presence or absence of pyramidal and cerebellar dysfunction with area under curve 0.840 (p < 0.001) and 0.829 (p < 0.001), respectively.

Conclusions

The BRAIN test can remotely measure disability in MS. Specific scores differ according to the presence and severity of pyramidal or extrapyramidal dysfunction. It demonstrates huge potential in monitoring disease progression in clinical trials.

Electronic supplementary material

The online version of this article (10.1007/s00415-017-8690-x) contains supplementary material, which is available to authorized users.

Technologies Assessing Limb Bradykinesia in Parkinson's Disease

Background: The MDS-UPDRS (Movement Disorders Society – Unified Parkinson’s Disease Rating Scale) is the most widely used scale for rating impairment in PD. Subscores measuring bradykinesia have low reliability that can be subject to rater variability. Novel technological tools can be used to overcome such issues.

Objective: To systematically explore and describe the available technologies for measuring limb bradykinesia in PD that were published between 2006 and 2016.

Methods: A systematic literature search using PubMed (MEDLINE), IEEE Xplore, Web of Science, Scopus and Engineering Village (Compendex and Inspec) databases was performed to identify relevant technologies published until 18 October 2016.

Results: 47 technologies assessing bradykinesia in PD were identified, 17 of which offered home and clinic-based assessment whilst 30 provided clinic-based assessment only. Of the eligible studies, 7 were validated in a PD patient population only, whilst 40 were tested in both PD and healthy control groups. 19 of the 47 technologies assessed bradykinesia only, whereas 28 assessed other parkinsonian features as well. 33 technologies have been described in additional PD-related studies, whereas 14 are not known to have been tested beyond the pilot phase.

Conclusion: Technology based tools offer advantages including objective motor assessment and home monitoring of symptoms, and can be used to assess response to intervention in clinical trials or routine care. This review provides an up-to-date repository and synthesis of the current literature regarding technology used for assessing limb bradykinesia in PD. The review also discusses the current trends with regards to technology and discusses future directions in development.

Objective Assessment of Bradykinesia Estimated from the Wrist Extension in Older Adults and Patients with Parkinson's Disease

Parkinson's disease (PD) presents several motor signs, including tremor and bradykinesia. However, these signs can also be found in other motor disorders and in neurologically healthy older adults. The incidence of bradykinesia in PD is relatively high in all stages of the disorder, even when compared to tremor. Thus, this research proposes an objective assessment of bradykinesia in patients with PD (G _PD: 15 older adults with Parkinson's disease, 65.3 ± 9.1 years) and older adults (G _HV: 12 healthy older adults, 60.1 ± 6.1 years). The severity of bradykinesia in the participants of G _PD was assessed using the Unified Parkinson's Disease Rating Scale. Movement and muscular activity were detected by means of inertial (accelerometer, gyroscope, magnetometer) and electromyographic sensors while the participants performed wrist extension against gravity with the forearm on pronation. Mean and standard error of inertial and electromyographic signal parameters could discriminate PD patients from healthy older adults (p value <0.05). In discriminating patients with PD from healthy older adults, the mean sensitivity and specificity were respectively 86.67 and 83.33%. The discrimination between the groups, based on the objective evaluation of bradykinesia, may contribute to the accurate diagnosis of PD and to the monitoring of therapies to control parkinsonian bradykinesia, and opens the possibility for further comparative studies considering individuals suffering from other motor disorders.

Study protocol: Insight 46 - a neuroscience sub-study of the MRC National Survey of Health and Development

BACKGROUND

Increasing age is the biggest risk factor for dementia, of which Alzheimer's disease is the commonest cause. The pathological changes underpinning Alzheimer's disease are thought to develop at least a decade prior to the onset of symptoms. Molecular positron emission tomography and multi-modal magnetic resonance imaging allow key pathological processes underpinning cognitive impairment - including β-amyloid depostion, vascular disease, network breakdown and atrophy - to be assessed repeatedly and non-invasively. This enables potential determinants of dementia to be delineated earlier, and therefore opens a pre-symptomatic window where intervention may prevent the onset of cognitive symptoms.

METHODS/DESIGN

This paper outlines the clinical, cognitive and imaging protocol of "Insight 46", a neuroscience sub-study of the MRC National Survey of Health and Development. This is one of the oldest British birth cohort studies and has followed 5362 individuals since their birth in England, Scotland and Wales during one week in March 1946. These individuals have been tracked in 24 waves of data collection incorporating a wide range of health and functional measures, including repeat measures of cognitive function. Now aged 71 years, a small fraction have overt dementia, but estimates suggest that ~1/3 of individuals in this age group may be in the preclinical stages of Alzheimer's disease. Insight 46 is recruiting 500 study members selected at random from those who attended a clinical visit at 60-64 years and on whom relevant lifecourse data are available. We describe the sub-study design and protocol which involves a prospective two time-point (0, 24 month) data collection covering clinical, neuropsychological, β-amyloid positron emission tomography and magnetic resonance imaging, biomarker and genetic information. Data collection started in 2015 (age 69) and aims to be completed in 2019 (age 73).

DISCUSSION

Through the integration of data on the socioeconomic environment and on physical, psychological and cognitive function from 0 to 69 years, coupled with genetics, structural and molecular imaging, and intensive cognitive and neurological phenotyping, Insight 46 aims to identify lifetime factors which influence brain health and cognitive ageing, with particular focus on Alzheimer's disease and cerebrovascular disease. This will provide an evidence base for the rational design of disease-modifying trials.

Subtle motor disturbances in PREDICT-PD participants

OBJECTIVE

The PREDICT-PD study aims to identify increased risk of Parkinson''s disease (PD) using online assessments of previously identified risk and early features of PD and an evidence-based scoring algorithm. We sought to determine whether higher risk participants (defined as those above the 15th centile of risk estimates) were more likely to have mild parkinsonian signs compared with lower risk participants.

METHODS

Video recordings of neurological examinations, including the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III, of 208 individuals who had previously completed an online risk assessment were scored blindly and independently by two movement-disorders experts. Higher risk and lower risk subjects were compared for MDS-UPDRS part III score (and derivations of this) to identify subclinical parkinsonism, and association of risk estimates with MDS-UPDRS III scores assessed.

RESULTS

Higher risk subjects had significantly higher median UPDRS part III scores (3, IQR 1-5.5) than lower risk subjects (1, IQR 0-3.0; p<0.001), and there was a significantly greater proportion of individuals classified as having subclinical parkinsonism. 18% of the higher risk subjects and 6% of the lower risk subjects exceeded the most stringent published cut-off for subtle parkinsonism of three definitions examined (p=0.027). Linear regression analysis demonstrated a continuous relationship of log-transformed risk estimates with UPDRS part III scores (increase in MDS-UPDRS per doubling of odds 0.52, 95% CI 0.31 to 0.72; p<0.001), which remained after adjustment for multiple vascular risk factors and scores on the Montreal Cognitive Assessment (0.58, 95% CI 0.30 to 0.87; p<0.001).

CONCLUSIONS

The PREDICT-PD algorithm identifies a population with an increased rate of motor disturbances.

Detection of Motor Impairment in Parkinson's Disease Via Mobile Touchscreen Typing

Mobile technology is opening a wide range of opportunities for transforming the standard of care for chronic disorders. Using smartphones as tools for longitudinally tracking symptoms could enable personalization of drug regimens and improve patient monitoring. Parkinson's disease (PD) is an ideal candidate for these tools. At present, evaluation of PD signs requires trained experts to quantify motor impairment in the clinic, limiting the frequency and quality of the information available for understanding the status and progression of the disease. Mobile technology can help clinical decision making by completing the information of motor status between hospital visits. This paper presents an algorithm to detect PD by analyzing the typing activity on smartphones independently of the content of the typed text. We propose a set of touchscreen typing features based on a covariance, skewness, and kurtosis analysis of the timing information of the data to capture PD motor signs. We tested these features, both independently and in a multivariate framework, in a population of 21 PD and 23 control subjects, achieving a sensitivity/specificity of 0.81/0.81 for the best performing feature and 0.73/0.84 for the best multivariate method. The results of the alternating finger-tapping, an established motor test, measured in our cohort are 0.75/0.78. This paper contributes to the development of a home-based, high-compliance, and high-frequency PD motor test by analysis of routine typing on touchscreens.

PREDICT-PD: An online approach to prospectively identify risk indicators of Parkinson's disease

Background

A number of early features can precede the diagnosis of Parkinson's disease (PD).

Objective

To test an online, evidence‐based algorithm to identify risk indicators of PD in the UK population.

Methods

Participants aged 60 to 80 years without PD completed an online survey and keyboard‐tapping task annually over 3 years, and underwent smell tests and genotyping for glucocerebrosidase (GBA) and leucine‐rich repeat kinase 2 (LRRK2) mutations. Risk scores were calculated based on the results of a systematic review of risk factors and early features of PD, and individuals were grouped into higher (above 15th centile), medium, and lower risk groups (below 85th centile). Previously defined indicators of increased risk of PD (“intermediate markers”), including smell loss, rapid eye movement–sleep behavior disorder, and finger‐tapping speed, and incident PD were used as outcomes. The correlation of risk scores with intermediate markers and movement of individuals between risk groups was assessed each year and prospectively. Exploratory Cox regression analyses with incident PD as the dependent variable were performed.

Results

A total of 1323 participants were recruited at baseline and >79% completed assessments each year. Annual risk scores were correlated with intermediate markers of PD each year and baseline scores were correlated with intermediate markers during follow‐up (all P values < 0.001). Incident PD diagnoses during follow‐up were significantly associated with baseline risk score (hazard ratio = 4.39, P = .045). GBA variants or G2019S LRRK2 mutations were found in 47 participants, and the predictive power for incident PD was improved by the addition of genetic variants to risk scores.

Conclusions

The online PREDICT‐PD algorithm is a unique and simple method to identify indicators of PD risk. © 2017 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

A Validation Study of a Smartphone-Based Finger Tapping Application for Quantitative Assessment of Bradykinesia in Parkinson's Disease

Background

Most studies of smartphone-based assessments of motor symptoms in Parkinson’s disease (PD) focused on gait, tremor or speech. Studies evaluating bradykinesia using wearable sensors are limited by a small cohort size and study design. We developed an application named smartphone tapper (SmT) to determine its applicability for clinical purposes and compared SmT parameters to current standard methods in a larger cohort.

Methods

A total of 57 PD patients and 87 controls examined with motor UPDRS underwent timed tapping tests (TT) using SmT and mechanical tappers (MeT) according to CAPSIT-PD. Subjects were asked to alternately tap each side of two rectangles with an index finger at maximum speed for ten seconds. Kinematic measurements were compared between the two groups.

Results

The mean number of correct tapping (MCoT), mean total distance of finger movement (T-Dist), mean inter-tap distance, and mean inter-tap dwelling time (IT-DwT) were significantly different between PD patients and controls. MCoT, as assessed using SmT, significantly correlated with motor UPDRS scores, bradykinesia subscores and MCoT using MeT. Multivariate analysis using the SmT parameters, such as T-Dist or IT-DwT, as predictive variables and age and gender as covariates demonstrated that PD patients were discriminated from controls. ROC curve analysis of a regression model demonstrated that the AUC for T-Dist was 0.92 (95% CI 0.88–0.96).

Conclusion

Our results suggest that a smartphone tapping application is comparable to conventional methods for the assessment of motor dysfunction in PD and may be useful in clinical practice.

Parkinson bradykinesia correlates with EEG background frequency and perceptual forward projection

BACKGROUND

To deal with processing-time in the nervous system, visuomotor control requires anticipation. An index for such anticipation is provided by the 'flash-lag illusion' in which moving objects are perceived ahead of static objects while actually being in the same place. We investigated the neurophysiological relation between visuomotor anticipation and motor velocity in Parkinson's disease (PD) and controls.

METHODS

Motor velocity was assessed by the number of keystrokes in 30s ('kinesia score') and visuomotor anticipation in a behavioural flash-lag paradigm while electroencephalography data was obtained. PD patients (n = 24) were divided in a 'PDslow' and a 'PDfast' group based on kinesia score.

RESULTS

The PDslow group had a lower kinesia score than controls (resp. 40.3 ± 1.7 and 64.9 ± 4.6, p < 0.001). The flash-lag illusion was weaker in the PDslow group than in controls (resp. fractions 0.32 ± 0.04 and 0.50 ± 0.09 of the responses indicating perceived lagging, p = 0.03). Furthermore, the magnitude of the flash-lag illusion correlated with the kinesia score (cc = 0.45, p = 0.02). Finally, electroencephalography background frequency was lower in the PDslow group than in controls (resp 8.24 ± 0.24 and 9.1 ± 0.32 Hz, p = 0.01) and background frequency correlated with the kinesia score (cc = 0.58, p = 0.001).

CONCLUSIONS

The decreased flash-lag illusion and lower electroencephalography background frequency in more bradykinetic PD patients provides support for disturbed visuomotor anticipations, putatively caused by reduced, sub-cortically mediated, network efficiency. This suggests a link between anticipation in early-stage visual motion processing and motor preparation.