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BackgroundMobile health, predominantly wearable technology and mobile apps, have been considered in Parkinson disease to provide valuable ecological data between face-to-face visits and improve monitoring of motor symptoms remotely. ObjectiveWe explored the feasibility of using a technology-based mHealth platform comprising a smartphone in combination with a smartwatch and a pair of smart insoles, described in this study as the PD_manager system, to collect clinically meaningful data. We also explored outcomes and disease-related factors that are important determinants to establish feasibility. Finally, we further validated a tremor evaluation method with data collected while patients performed their daily activities. MethodsPD_manager trial was an open-label parallel group randomized study.The mHealth platform consists of a wristband, a pair of sensor insoles, a smartphone (with dedicated mobile Android apps) and a knowledge platform serving as the cloud backend. Compliance was assessed with statistical analysis and the factors affecting it using appropriate regression analysis. The correlation of the scores of our previous algorithm for tremor evaluation and the respective Unified Parkinson’s Disease Rating Scale estimations by clinicians were explored. ResultsOf the 75 study participants, 65 (87%) completed the protocol. They used the PD_manager system for a median 11.57 (SD 3.15) days. Regression analysis suggests that the main factor associated with high use was caregivers’ burden. Motor Aspects of Experiences of Daily Living and patients’ self-rated health status also influence the system’s use. Our algorithm provided clinically meaningful data for the detection and evaluation of tremor. ConclusionsWe found that PD patients, regardless of their demographics and disease characteristics, used the system for 11 to 14 days. The study further supports that mHealth can be an effective tool for the ecologically valid, passive, unobtrusive monitoring and evaluation of symptoms. Future studies will be required to demonstrate that an mHealth platform can improve disease management and care. Trial RegistrationISRCTN Registry ISRCTN17396879; http://www.isrctn.com/ISRCTN17396879 International Registered Report Identifier (IRRID)RR2-10.1186/s13063-018-2767-4

Background: The Parkinson's Disease-Cognitive Rating Scale (PD-CRS) is a comprehensive screening procedure for the evaluation of cognitive impairment in patients with Parkinson's disease (PD). Objectives: In the present study we adjusted the PD-CRS for the Greek population, developed normative data and examined its clinical utility for the assessment of cognitive functioning in Greek PD patients. In addition, the correlation of clinical characteristics with cognitive performance in PD patients was examined. Methods: Three hundred four community-dwelling healthy adults and 59 patients with PD, completed the adapted PD-CRS. Results: Healthy adults outperformed the PD patients on the total, the cortical and subcortical scores of the PD-CRS. Normative data indicated effects of both education and age on the PD-CRS. The optimal total PD-CRS cutoff score for the identification of cognitive impairment in a heterogeneous sample of PD patients, with regard to the severity of cognitive difficulties, was 79, yielding a modest sensitivity and specificity. Clinical characteristics of the patients (i.e., disease duration and functional disease burden) were related to poor performance on the PD-CRS. Conclusions: The Greek version of the PD-CRS is a useful instrument for the assessment of cognition in PD. Future prospective studies should examine its clinical utility to identify PD-cognitive subtypes (i.e., PD patients with mild cognitive impairment), to monitor cognitive changes, as well as its predictive accuracy for subsequent dementia. [ABSTRACT FROM AUTHOR]

Purpose of the study: The multimodal imaging investigation of excessive daytime sleepiness (EDS) in Parkinson's disease (PD). The role of dopaminergic treatment and other clinical parameters was also evaluated.Materials and methods: Seventeen non-demented PD patients with EDS (PD-EDS) and 17 PD patients without EDS were enrolled. Clinical, treatment and MRI data were acquired. Gray matter (GM) volume was examined with voxel-based morphometry, while white matter (WM) integrity was assessed with diffusion tensor imaging by means of fractional anisotropy, mean diffusivity, axial diffusivity (AD) and radial diffusivity measures.Results: Increased regional GM volume was found in the PD-EDS group bilaterally in the hippocampus and parahippocampal gyri. Increased AD values were also shown in the PD-EDS group, in the left anterior thalamic radiation and the corticospinal tract and bilaterally in the superior corona radiata and the superior longitudinal fasciculus. Levodopa equivalent dose differed significantly between the groups and was the only predictor of EDS, while the only predictor of the Epworth sleepiness scale score in the PD-EDS group was the dopamine-agonist dose. Increased frequency of gamblers was also observed in the PD-EDS group.Conclusions: Regional GM increases and increased AD values in certain WM tracts were found in the PD-EDS group. The changes could result from disinhibited signaling pathways or represent compensatory changes in response to anatomical or functional deficits elsewhere. The study findings support also the contribution of the total dopaminergic load in the development of EDS, while the dose of dopamine agonists was found to predict the severity of the disorder. [ABSTRACT FROM PUBLISHER]

Freezing of Gait (FoG) is a common symptom in Parkinson's Disease (PD) occurring with significant variability and severity and is associated with increased risk of falls. FoG detection in everyday life is not trivial, particularly in patients manifesting the symptom only in specific conditions. Various wearable devices have been proposed to detect PD symptoms, primarily based on inertial sensors. We here report the results of the validation of a novel system based on a pair of pressure insoles equipped with a 3D accelerometer to detect FoG episodes. Twenty PD patients attended a motor assessment protocol organized into eight multiple video recorded sessions, both in clinical and ecological settings and both in the ON and OFF state. We compared the FoG episodes detected using the processed data gathered from the insoles with those tagged by a clinician on video recordings. The algorithm correctly detected 90% of the episodes. The false positive rate was 6% and the false negative rate 4%. The algorithm reliably detects freezing of gait in clinical settings while performing ecological tasks. This result is promising for freezing of gait detection in everyday life via wearable instrumented insoles that can be integrated into a more complex system for comprehensive motor symptom monitoring in PD. [ABSTRACT FROM AUTHOR]

In this paper, a method for the assessment of the Unified Parkinson Disease Rating scale (UPDRS) related to tremor is presented. The method described consists of hand resting and posture state detection, tremor detection and tremor quantification based on accelerometer and gyroscope readings from a wrist worn sensor. The initial results on PD patient recordings on home environment indicate the feasibility of the proposed method in monitoring UPDRS tremor in patient home environment.

Parkinson's disease (PD) is a complex, chronic disease that many patients live with for many years. In this work we propose a mHealth approach based on a set of unobtrusive, simple-in-use, off-the-self, co-operative, mobile devices that will be used for motor and non-motor symptoms monitoring and evaluation, as well as for the detection of fluctuations along with their duration through a waking day. Ideally, a multidisciplinary and integrated care approach involving several professionals working together (neurologists, physiotherapists, psychologists and nutritionists) could provide a holistic management of the disease increasing the patient's independence and Quality of Life (QoL). To address these needs we describe also an ecosystem for the management of both motor and non-motor symptoms on PD facilitating the collaboration of health professionals and empowering the patients to self-manage their condition. This would allow not only a better monitoring of PD patients but also a better understanding of the disease progression.

The ALZCARE project aims at assisting people at risk or already suffering of dementia, their family and health professionals in the dementia care pathway by providing an integrated ICT-enabled information System. The system consists of a mobile platform for screening people at risk, a Clinical Information System and a satellite-based patient tracking system. The system is currently on the evaluation phase focusing on addressing the needs of citizens of the cross-border areas of Greece and Albania.