Continuous quantitative monitoring of physical activity in Parkinson's disease patients by using wearable devices: a case-control study

Influence of cognitive reserve on cognitive and motor function in α-synucleinopathies: A systematic review and multilevel meta-analysis

Cognitive reserve has shown promise as a justification for neuropathologically unexplainable clinical outcomes in Alzheimer's disease. Recent evidence suggests this effect may be replicated in conditions like Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. However, the relationships between cognitive reserve and different cognitive abilities, as well as motor outcomes, are still poorly understood in these conditions. Additionally, it is unclear whether the reported effects are confounded by medication. This review analysed studies investigating the relationship between cognitive reserve and clinical outcomes in these α-synucleinopathy cohorts, identified from MEDLINE, Scopus, psycINFO, CINAHL, and Web of Science. 85 records, containing 176 cognition and 31 motor function effect sizes, were pooled using multilevel meta-analysis. There was a significant, positive association between higher cognitive reserve and both better cognition and motor function. Cognition effect sizes differed by disease subtype, cognitive reserve measure, and outcome type; however, no moderators significantly impacted motor function. Review findings highlight the clinical implications of cognitive reserve and importance of engaging in reserve-building behaviours.

Objective Measurement of Walking Activity Using Wearable Technologies in People with Parkinson Disease: A Systematic Review

Parkinson’s disease (PD) is a complex neurodegenerative disease with a multitude of disease variations including motor and non-motor symptoms. Quality of life and symptom management may be improved with physical activity. Due to technological advancement, development of small new wearable devices recently emerged and allowed objective measurement of walking activity in daily life. This review was specifically designed to synthesize literature on objective walking activity measurements using wearable devices of patients with PD. Inclusion criteria included patients with a diagnosis of PD and exclusion criteria included studies using animal models or mixed syndromes. Participants were not required to undergo any type of intervention and the studies must have reported at least one output that quantifies daily walking activity. Three databases were systematically searched with no limitation on publication date. Twenty-six studies were eligible and included in the systematic review. The most frequently used device was the ActiGraph GT3X which was used in 10 studies. Duration of monitoring presented a range from 8 h to one year. Nevertheless, 11 studies measured walking activity during a 7-day period. On-body sensor wearing location differed throughout the included studies showing eight positions, with the waist, ankle, and wrist being the most frequently used locations. The main procedures consisted of measurement of walking hours during a 2-day period or more, equipped with a triaxial accelerometer at the dominant hip or ankle. It is also important for further research to take care of different factors such as the population, their pathology, the period, and the environment.

Effectiveness of Telerehabilitation on Motor Impairments, Non-motor Symptoms and Compliance in Patients With Parkinson's Disease: A Systematic Review

Introduction: Parkinson's disease (PD) is a chronic neurodegenerative disease involving a progressive alteration of the motor and non-motor function. PD influences the patient's daily living and reduces participation and quality of life in all phases of the disease. Early physical exercise can mitigate the effects of symptoms but access to specialist care is difficult. With current technological progress, telemedicine, and telerehabilitation is now a viable option for managing patients, although few studies have investigated the use of telerehabilitation in PD. In this systematic review, was investigated whether telerehabilitation leads to improvements in global or specific motor tasks (gait and balance, hand function) and non-motor dysfunction (motor speech disorder, dysphagia). The impact of TR on quality of life and patient satisfaction, were also assessed. The usage of telerehabilitation technologies in the management of cognitive impairment was not addressed.

Method: An electronic database search was performed using the following databases: PubMed/MEDLINE, COCHRANE Library, PEDro, and SCOPUS for data published between January 2005 and December 2019 on the effects of telerehabilitation systems in managing motor and non-motor symptoms. This systematic review was conducted in accordance with the PRISMA guideline and was registered in the PROSPERO database (CRD42020141300).

Results: A total of 15 articles involving 421 patients affected by PD were analyzed. The articles were divided into two categories based on their topic of interest or outcome. The first category consisted of the effects of telerehabilitation on gait and balance (3), dexterity of the upper limbs (3), and bradykinesia (0); the second category regarded non-motor symptoms such as speech disorders (8) and dysphagia (0). Quality of life (7) and patient satisfaction (8) following telerehabilitation programs were also analyzed, as well as feasibility and costs.

Conclusion: Telerehabilitation is feasible in people affected by PD. Our analysis of the available data highlighted that telerehabilitation systems are effective in maintaining and/or improving some clinical and non-clinical aspects of PD (balance and gait, speech and voice, quality of life, patient satisfaction).

Systematic Review Registration:https://www.crd.york.ac.uk/prospero/, identifier: CRD42020141300.

A wearable tool for continuous monitoring of movement disorders: clinical assessment and comparison with tremor scores

BACKGROUND

The current gold standard for evaluating normal and impaired motor performances includes the use of the information provided by the patient and the Unified Parkinson's Disease Rating Scale (UPDRS). However, clinical rating scales are typically subjective and their time-limited duration may fail to capture daily fluctuations in motor symptoms resulting from Parkinson's disease. Recently, a new tool has been proposed for objective and continuous assessment of movement disorders based on the evaluation of frequential data content from multi-axial sensors and the identification of specific movement patterns typically associated with disorders. This reduces the probability of confusing physiological or pathological movements occurring at the same frequency with a different movement pattern. However, the data provided by the tool have not yet been compared with the information provided by the typically used clinical rating scales.

OBJECTIVES

The aim of this work is to investigate the possible relationship between UPRDS scores and the information provided by the tool for continuous and long-term monitoring.

MATERIALS AND METHODS

In this study, 20 patients with hand tremor were recruited. The UPDRS scoring was performed by a neurologist. Then, continuous monitoring was performed; data were acquired by means of the proposed wrist-worn-device "PD-Watch" for 24 h and then processed in order to get information and indexes on motor symptoms. Finally, these indexes were correlated to the UPDRS scores.

RESULTS

Results show that the concise indexes provided by the tool correlate well with some items in UPDRS Part III, and this correlation has allowed to provide a more direct and immediate meaning to the values of the concise indexes detected by the tool.

CONCLUSIONS

While results need to be extended with further studies, this can be considered useful information in the context of clinical trials and routine clinical practice for assessing motor symptoms and movement disorders.

Body-Worn Sensors for Remote Monitoring of Parkinson's Disease Motor Symptoms: Vision, State of the Art, and Challenges Ahead

The increasing prevalence of neurodegenerative conditions such as Parkinson's disease (PD) and related mobility issues places a serious burden on healthcare systems. The COVID-19 pandemic has reinforced the urgent need for better tools to manage chronic conditions remotely, as regular access to clinics may be problematic. Digital health technology in the form of remote monitoring with body-worn sensors offers significant opportunities for transforming research and revolutionizing the clinical management of PD. Significant efforts are being invested in the development and validation of digital outcomes to support diagnosis and track motor and mobility impairments "off-line". Imagine being able to remotely assess your patient, understand how well they are functioning, evaluate the impact of any recent medication/intervention, and identify the need for urgent follow-up before overt, irreparable change takes place? This could offer new pragmatic solutions for personalized care and clinical research. So the question remains: how close are we to achieving this? Here, we describe the state-of-the-art based on representative papers published between 2017 and 2020. We focus on remote (i.e., real-world, daily-living) monitoring of PD using body-worn sensors (e.g., accelerometers, inertial measurement units) for assessing motor symptoms and their complications. Despite the tremendous potential, existing challenges exist (e.g., validity, regulatory) that are preventing the widespread clinical adoption of body-worn sensors as a digital outcome. We propose a roadmap with clear recommendations for addressing these challenges and future directions to bring us closer to the implementation and widespread adoption of this important way of improving the clinical care, evaluation, and monitoring of PD.

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.

The effects of exercise on sleep quality in persons with Parkinson's disease: A systematic review with meta-analysis

We conducted a systematic review with meta-analysis to determine the evidence in support of exercise to improve sleep quality assessed subjectively and objectively in Parkinson's Disease (PD). Standardized mean differences (SMD) comparing the effects of exercise and control interventions on sleep quality with 95% confidence intervals (CI) were calculated. Data from 10 randomized and 2 non-randomized controlled trials, including a total of 690 persons with PD were included. Exercise had a significant positive effect on sleep quality assessed subjectively (SMD = 0.53; 95% CI = 0.16-0.90; p = 0.005). However, the methodological quality of the studies showing positive effects on sleep quality was significantly poorer than the studies showing no effects. Only one study assessed the impact of exercise on objective sleep quality, showing improvements in sleep efficiency assessed with polysomnography (SMD = 0.94; 95% CI = 0.38-1.50; p = 0.001). Exercise performed at moderate to maximal intensities (SMD = 0.46; 95% CI = 0.05-0.87; p = 0.03) had significant effects on subjective sleep quality. In contrast, exercise performed at mild to moderate intensities showed non-significant effects (SMD = 0.76; 95% CI = -0.24-1.76; p = 0.14). These results support the use of exercise to improve sleep quality in persons with PD and reinforce the importance of achieving vigorous exercise intensities. Biases, limitations, practice points and directions for future research are discussed.

Muscle echo intensity of abdominal wall in Parkinson's disease and healthy controls: a cross sectional study

PURPOSE

The aim of this study was to describe the differences between abdominal wall muscles echo intensity (EI) in PD patients and healthy controls.

METHODS

Forty-three consecutive PD patients (25 males and 18 females, age 73.7 ± 7.1, and 42 controls without neurological diseases (22 males, 20 females, age 69.8 ± 6.0) participated in this cross-sectional study. The clinical assessment included the following: IPAQ (International Physical Activity Questionnaire), Hoehn Yahr score, plumb line distance from the spinous process of C7, kyphosis apex, and spinous process of L3 and S1. A real-time ultrasound B-scanner (system MyLab40 by Esaote, Genoa, Italy) was used to obtain muscle images of the right and left biceps brachii (BB), external (EO), and internal oblique (IO) and rectus abdomen (RA). Heckmatt scale and measure of EI through ImageJ software were used to assess muscle quality.

RESULTS

When considering the Heckmatt score, the RA and BB did not significantly differ between PD and control patients, while there was a significant difference for right (p < 0.01) and left (p = 0.02) IO muscles. There was no difference among EI values of the RA, IO, and BB between PD and control patients.

CONCLUSIONS

Echo intensity of abdominal wall muscles (rectus abdominis, internal oblique) and biceps brachii did not differ between Parkinsonian patients and healthy subjects. We did not found ultrasound useful in disease evolution assessment or in early diagnosis of postural disorders.

What Determines Spontaneous Physical Activity in Patients with Parkinson's Disease?

Physical activity (PA) is a factor that may have an influence on the symptoms of Parkinson's disease (PD). The aim of this study was to identify the potential determinants of spontaneous PA in a PD patient group. A total of 134 PD patients aged 65.2 ± 9.2 years with a Hoehn-Yahr scale score ≤4 and a Mini Mental State Examination (MMSE) score ≥24 were examined. For the study's purposes, the authors analyzed age, sex, education, history of PD, dopaminergic treatment, the severity of PD symptoms using Unified Parkinson's Disease Rating Scale (UPDRS), and Hoehn-Yahr scale. Additionally, all participants were evaluated through a set of scales for specific neuropsychiatric symptoms including depression, anxiety, apathy, fatigue, and sleep disorders. A linear regression analysis was used with backward elimination. In the total explanatory model, for 12% of the variability in activity (R² = 0.125; F(16.133) = 2.185; p < 0.01), the significant predictor was starting therapy with the dopamine agonist (DA) (β= 0.420; t= 4.068; p = 0.000), which was associated with a longer duration of moderate PA. In the total explanatory model, for more than 13% of the variance in time spent sitting (R² = 0.135; F(16.130) = 2.267; p < 0.01), the significant predictors were secondary education and the results of the UPDRS. The patients with secondary and vocational education, those starting treatment with DA and those with a less severe degree of Parkinson's symptoms (UPDRS), spent less time sitting in a day. It is possible to identify determinants of spontaneous PA. It may elucidate consequences in terms of influence on modifiable conditions of PA and the proper approach to patients with unmodifiable PA factors.

Accuracy and Precision of Three Consumer-Grade Motion Sensors During Overground and Treadmill Walking in People With Parkinson Disease: Cross-Sectional Comparative Study

BACKGROUND

Wearable motion sensors are gaining popularity for monitoring free-living physical activity among people with Parkinson disease (PD), but more evidence supporting the accuracy and precision of motion sensors for capturing step counts is required in people with PD.

OBJECTIVE

This study aimed to examine the accuracy and precision of 3 common consumer-grade motion sensors for measuring actual steps taken during prolonged periods of overground and treadmill walking in people with PD.

METHODS

A total of 31 ambulatory participants with PD underwent 6-min bouts of overground and treadmill walking at a comfortable speed. Participants wore 3 devices (Garmin Vivosmart 3, Fitbit One, and Fitbit Charge 2 HR), and a single researcher manually counted the actual steps taken. Accuracy and precision were based on absolute and relative metrics, including intraclass correlation coefficients (ICCs) and Bland-Altman plots.

RESULTS

Participants walked 628 steps over ground based on manual counting, and Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR devices had absolute (relative) error values of 6 (6/628, 1.0%), 8 (8/628, 1.3%), and 30 (30/628, 4.8%) steps, respectively. ICC values demonstrated excellent agreement between manually counted steps and steps counted by both Garmin Vivosmart (0.97) and Fitbit One (0.98) but poor agreement for Fitbit Charge 2 HR (0.47). The absolute (relative) precision values for Garmin Vivosmart, Fitbit One, and Fitbit Charge 2 HR were 11.1 (11.1/625, 1.8%), 14.7 (14.7/620, 2.4%), and 74.4 (74.4/598, 12.4%) steps, respectively. ICC confidence intervals demonstrated low variability for Garmin Vivosmart (0.96 to 0.99) and Fitbit One (0.93 to 0.99) but high variability for Fitbit Charge 2 HR (-0.57 to 0.74). The Fitbit One device maintained high accuracy and precision values for treadmill walking, but both Garmin Vivosmart and Fitbit Charge 2 HR (the wrist-worn devices) had worse accuracy and precision for treadmill walking.

CONCLUSIONS

The waist-worn sensor (Fitbit One) was accurate and precise in measuring steps with overground and treadmill walking. The wrist-worn sensors were accurate and precise only during overground walking. Similar research should inform the application of these devices in clinical research and practice involving patients with PD.

Systematic Review Looking at the Use of Technology to Measure Free-Living Symptom and Activity Outcomes in Parkinson's Disease in the Home or a Home-like Environment

BACKGROUND

The emergence of new technologies measuring outcomes in Parkinson's disease (PD) to complement the existing clinical rating scales has introduced the possibility of measurement occurring in patients' own homes whilst they freely live and carry out normal day-to-day activities.

OBJECTIVE

This systematic review seeks to provide an overview of what technology is being used to test which outcomes in PD from free-living participant activity in the setting of the home environment. Additionally, this review seeks to form an impression of the nature of validation and clinimetric testing carried out on the technological device(s) being used.

METHODS

Five databases (Medline, Embase, PsycInfo, Cochrane and Web of Science) were systematically searched for papers dating from 2000. Study eligibility criteria included: adults with a PD diagnosis; the use of technology; the setting of a home or home-like environment; outcomes measuring any motor and non-motor aspect relevant to PD, as well as activities of daily living; unrestricted/unscripted activities undertaken by participants.

RESULTS

65 studies were selected for data extraction. There were wide varieties of participant sample sizes (<10 up to hundreds) and study durations (<2 weeks up to a year). The metrics evaluated by technology, largely using inertial measurement units in wearable devices, included gait, tremor, physical activity, bradykinesia, dyskinesia and motor fluctuations, posture, falls, typing, sleep and activities of daily living.

CONCLUSIONS

Home-based free-living testing in PD is being conducted by multiple groups with diverse approaches, focussing mainly on motor symptoms and sleep.

Exercise and Parkinson's Disease

Parkinson's disease (PD) is an aging-related neurodegenerative disorder characterized by progressive motor impairment.The etiology of PD is poorly understood but likely involves both genetic and environmental factors; the management of the disease is still with symptomatic therapy without any interference on the progression of neurodegeneration. In the past two decades, the results of a series of prospective cohort studies suggested that lifestyle factors likely modify the risk of developing PD. Among these, physical activity is known to reduce the risk of a wide range of diseases and conditions, including cardiovascular disease, stroke, and diabetes.Recently, a growing body of evidence has suggested that increased physical activity may also reduce the risk of PD and partly improve motor and non-motor symptoms during the disease course.Here we report the main findings on the effect of physical activity on both mobility and cognition either in animal models of PD or in people with PD. We also highlighted the structural and functional links between gait and cognition by reporting evidence from neuroimaging studies.

Taking Systems Medicine to Heart

Systems medicine is a holistic approach to deciphering the complexity of human physiology in health and disease. In essence, a living body is constituted of networks of dynamically interacting units (molecules, cells, organs, etc) that underlie its collective functions. Declining resilience because of aging and other chronic environmental exposures drives the system to transition from a health state to a disease state; these transitions, triggered by acute perturbations or chronic disturbance, manifest as qualitative shifts in the interactions and dynamics of the disease-perturbed networks. Understanding health-to-disease transitions poses a high-dimensional nonlinear reconstruction problem that requires deep understanding of biology and innovation in study design, technology, and data analysis. With a focus on the principles of systems medicine, this Review discusses approaches for deciphering this biological complexity from a novel perspective, namely, understanding how disease-perturbed networks function; their study provides insights into fundamental disease mechanisms. The immediate goals for systems medicine are to identify early transitions to cardiovascular (and other chronic) diseases and to accelerate the translation of new preventive, diagnostic, or therapeutic targets into clinical practice, a critical step in the development of personalized, predictive, preventive, and participatory (P4) medicine.

Quantifying physical activity in early Parkinson disease using a commercial activity monitor

INTRODUCTION

Physical inactivity in Parkinson disease (PD) has an impact on motor and non-motor symptoms of the disease. It is unclear whether this decline in physical activity occurs early in the disease, in addition to any decline due to aging, and whether commercial activity monitors can be used to self-monitor physical activity levels in this population.

OBJECTIVE

To compare the quantity and intensity of physical activity (PA), as measured by commercial activity monitors, in people with mild PD and healthy older adults (HOA). A secondary objective was to assess adherence and user experience with wearing the activity monitoring device.

METHODS

An observational descriptive study design examined PA levels over a 14-day period using commercially-available activity monitors (Fitbit Charge HR).

RESULTS

Individuals with PD (n = 30) and HOA (n = 30) both demonstrated high adherence with wear time (PD = 13.8 [0.5] days, HOA = 13.9 [0.4] days, p = 0.55). People with PD took fewer steps per day than HOA (PD = 6416.9 (2795.5), HOA = 11441.3 (3932.1), p < 0.001). Compared to HOA, individuals with PD spent fewer minutes per day engaged in moderate to vigorous intensity activity (PD = 33.0 (22.5), HOA = 72.0(37.3), p < 0.001) and more minutes per day sedentary (PD = 803.74 (154.9), HOA = 578.26 (103.7), p < 0.001). Both groups reported that ease of use and satisfaction with the activity monitor were high.

CONCLUSIONS

People with mild PD demonstrated reduced quantity and intensity of PA compared to HOA. Both the PD and the HOA groups had good adherence wearing a commercial activity monitor that provided feedback regarding activity levels.

Association between Objectively Measured Physical Activity and Gait Patterns in People with Parkinson's Disease: Results from a 3-Month Monitoring

Background

Although physical activity (PA) is known to be beneficial in improving motor symptoms of people with Parkinson's disease (pwPD), little is known about the relationship between gait patterns and features of PA performed during daily life.

Objective

To verify the existence of possible relationships between spatiotemporal and kinematic parameters of gait and amount/intensity of PA, both instrumentally assessed.

Methods

Eighteen individuals affected by PD (10F and 8M, age 68.0 ± 10.8 years, 1.5 ≤ Hoehn and Yahr (H&Y) < 3) were required to wear a triaxial accelerometer 24 h/day for 3 consecutive months. They also underwent a 3D computerized gait analysis at the beginning and end of the PA assessment period. The number of daily steps and PA intensity were calculated on the whole day, and the period from 6:00 to 24:00 was grouped into 3 time slots, using 3 different cut-point sets previously validated in the case of both pwPD and healthy older adults. 3D gait analysis provided spatiotemporal and kinematic parameters of gait, including summary indexes of quality (Gait Profile Score (GPS) and Gait Variable Score (GVS)).

Results

The analysis of hourly trends of PA revealed the existence of two peaks located in the morning (approximately at 10) and in the early evening (between 18 and 19). However, during the morning time slot (06:00–12:00), pwPD performed significantly higher amounts of steps (4313 vs. 3437 in the 12:00–18:00 time slot, p < 0.001, and vs. 2889 in the 18:00–24:00 time slot, p=0.021) and of moderate-to-vigorous PA (43.2% vs. 36.3% in the 12:00–18:00 time slot, p=0.002, and vs. 31.4% in the 18:00–24:00 time slot, p=0.049). The correlation analysis shows that several PA intensity parameters are significantly associated with swing-phase duration (rho = −0.675 for sedentary intensity, rho = 0.717 for moderate-to-vigorous intensity, p < 0.001), cadence (rho = 0.509 for sedentary intensity, rho = −0.575 for moderate-to-vigorous intensity, p < 0.05), and overall gait pattern quality as expressed by GPS (rho = −0.498 to −0.606 for moderate intensity, p < 0.05) and GVS of knee flexion-extension (rho = −0.536 for moderate intensity, p < 0.05).

Conclusions

Long-term monitoring of PA integrated by the quantitative assessment of spatiotemporal and kinematic parameters of gait may represent a useful tool in supporting a better-targeted prescription of PA and rehabilitative treatments in pwPD.

Acceptability to patients, carers and clinicians of an mHealth platform for the management of Parkinson's disease (PD_Manager): study protocol for a pilot randomised controlled trial

BACKGROUND

Parkinson's disease is a degenerative neurological condition causing multiple motor and non-motor symptoms that have a serious adverse effect on quality of life. Management is problematic due to the variable and fluctuating nature of symptoms, often hourly and daily. The PD_Manager mHealth platform aims to provide a continuous feed of data on symptoms to improve clinical understanding of the status of any individual patient and inform care planning. The objectives of this trial are to (1) assess patient (and family carer) perspectives of PD_Manager regarding comfort, acceptability and ease of use; (2) assess clinician views about the utility of the data generated by PD_Manager for clinical decision making and the acceptability of the system in clinical practice.

METHODS/DESIGN

This trial is an unblinded, parallel, two-group, randomised controlled pilot study. A total of 200 persons with Parkinson's disease (Hoehn and Yahr stage 3, experiencing motor fluctuations at least 2 h per day), with primary family carers, in three countries (110 Rome, 50 Venice, Italy; 20 each in Ioannina, Greece and Surrey, England) will be recruited. Following informed consent, baseline information will be gathered, including the following: age, gender, education, attitudes to technology (patient and carer); time since Parkinson's diagnosis, symptom status and comorbidities (patient only). Randomisation will assign participants (1:1 in each country), to PD_Manager vs control, stratifying by age (1 ≤ 70 : 1 > 70) and gender (60% M: 40% F). The PD_Manager system captures continuous data on motor symptoms, sleep, activity, speech quality and emotional state using wearable devices (wristband, insoles) and a smartphone (with apps) for storing and transmitting the information. Control group participants will be asked to keep a symptom diary covering the same elements as PD_Manager records. After a minimum of two weeks, each participant will attend a consultation with a specialist doctor for review of the data gathered (by either means), and changes to management will be initiated as indicated. Patients, carers and clinicians will be asked for feedback on the acceptability and utility of the data collection methods. The PD_Manager intervention, compared to a symptom diary, will be evaluated in a cost-consequences framework.

DISCUSSION

Information gathered will inform further development of the PD_Manager system and a larger effectiveness trial.

TRIAL REGISTRATION

ISRCTN Registry, ISRCTN17396879 . Registered on 15 March 2017.

A novel device for continuous monitoring of tremor and other motor symptoms

The clinical assessment of Parkinson's disease (PD) symptoms is typically performed with neurological examinations and simple motor tests. However, this only takes into account the severity of motor symptoms during the length of the recording and fails to capture variations in a patient's motor state, which change continuously during the day. Most of the current methods for long-term monitoring of extrapyramidal symptoms are based on the use of a wearable magneto-inertial device that evaluates the frequential content of signals in the range of movement disorders. However, the typical daily motor activities performed by patients may have a power spectrum into the same range of motor symptoms, and habitual activity may be indistinguishable from that due to movement disorders. In this work, we report a new device and method for the continuous and long-term monitoring of tremor due to PD and other movement disorders to reduce the probability of mistaking the discrimination between extrapyramidal symptoms and normal daily activity. The method is based on the evaluation of frequential data content from multi-axial sensors and on the identification of specific movement patterns that Parkinsonian and extrapyramidal symptoms are typically associated with. In this study, 16 patients with movement disorders were recruited. While results need to be extended with further studies and clinical trials, the proposed device appears promising and suitable for the use as part of clinical trials and routine clinical practice for supporting the evaluation of motor symptoms, disease progression, and the quantification of therapeutic effects.

Impact of motor fluctuations on real-life gait in Parkinson's patients

BACKGROUND

People with PD (PWP) have an increased risk of becoming inactive. Wearable sensors can provide insights into daily physical activity and walking patterns.

RESEARCH QUESTIONS

(1) Is the severity of motor fluctuations associated with sensor-derived average daily walking quantity? (2) Is the severity of motor fluctuations associated with the amount of change in sensor-derived walking quantity after levodopa intake?

METHODS

304 Dutch PWP from the Parkinson@Home study were included. At baseline, all participants received a clinical examination. During the follow-up period (median: 97 days; 25-Interquartile range-IQR: 91 days, 75-IQR: 188 days), participants used the Fox Wearable Companion app and streamed smartwatch accelerometer data to a cloud platform. The first research question was assessed by linear regression on the sensor-derived mean time spent walking/day with the severity of fluctuations (MDS-UPDRS item 4.4) as independent variable, controlled for age and MDS-UPDRS part-III score. The second research question was assessed by linear regression on the sensor-derived mean post-levodopa walking quantity, with the sensor-derived mean pre-levodopa walking quantity and severity of fluctuations as independent variables, controlled for mean time spent walking per day, age and MDS-UPDRS part-III score.

RESULTS

PWP spent most time walking between 8am and 1pm, summing up to 72 ± 39 (mean ± standard deviation) minutes of walking/day. The severity of motor fluctuations did not influence the mean time spent walking (B = 2.4 ± 1.9, p = 0.20), but higher age (B = -1.3 ± 0.3, p = < 0.001) and greater severity of motor symptoms (B = -0.6 ± 0.2, p < 0.001) was associated with less time spent walking (F(3216) = 14.6, p < .001, R² = .17). The severity of fluctuations was not associated with the amount of change in time spent walking in relation to levodopa intake in any part of the day.

SIGNIFICANCE

Analysis of sensor-derived gait quantity suggests that the severity of motor fluctuations is not associated with changes in real-life walking patterns in mildly to moderate affected PWP.