A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders

Abstract

Parkinson's disease and Essential Tremor are two of the most common movement disorders and are still associated with high rates of misdiagnosis. Collected data by technology-based objective measures (TOMs) has the potential to provide new promising and highly accurate movement data for a better understanding of phenotypical characteristics and diagnostic support. A technology-based system called Smart Device System (SDS) is going to be implemented for multi-modal high-resolution acceleration measurement of patients with PD or ET within a clinical setting. The 2-year prospective observational study is conducted to identify new phenotypical biomarkers and train an Artificial Intelligence System. The SDS is going to be integrated and tested within a 20-min assessment including smartphone-based questionnaires, two smartwatches at both wrists and tablet-based Archimedean spirals drawing for deeper tremor-analyses. The electronic questionnaires will cover data on medication, family history and non-motor symptoms. In this paper, we describe the steps for this novel technology-utilizing examination, the principal steps for data analyses and the targeted performances of the system. Future work considers integration with Deep Brain Stimulation, dissemination into further sites and patient's home setting as well as integration with further data sources as neuroimaging and biobanks. Study Registration ID on ClinicalTrials.gov: NCT03638479.

Feasibility and Utility of mHealth for the Remote Monitoring of Parkinson Disease: Ancillary Study of the PD_manager Randomized Controlled Trial

“…Moreover, our findings are consistent with the Movement Disorder Society Task Force on Technology roadmap [ 20 ] as well as with patient attitudes on technology use [ 21 ]. Our mHealth platform, as relevant studies suggest, can be an effective tool for the passive, unobtrusive monitoring and evaluation of symptoms [ 22 ], defining new phenotypical biomarkers [ 23 ], detection of serious events such as falls [ 24 ], detection of worsening in the overall health status of the patients, and the provision of better disease management and improved care [ 25 ], the latter being already extensively studied in ongoing clinical trials (eg, NCT03741920 and NCT02657655). mHealth may also help rehabilitation [ 26 , 27 ] and facilitate telemedicine since it enables home-based [ 28 ], multidisciplinary [ 29 ] approaches for the management of PD.…”

Sensor Validation and Diagnostic Potential of Smartwatches in Movement Disorders

“…It is being conducted at the outpatient clinic of Movement Disorders at the University Hospital Münster in Germany. The details of the study design and the protocol have been published previously [13]. Study registration ID on Clinical-Trials.gov: NCT03638479.…”

“…Our research focusses on acceleration-based hand movement analyses using the Smart Device System (SDS) that is currently part of a prospective human subject trial [13]. The study has recruited and measured >350 participants and has generated one of the largest databases for PD, differential diagnoses and healthy subjects with acceleration data from a neurological examination including left and right side of the body and structured clinical data on non-motor symptoms (e.g.…”

Development and Validation of a New Wearable Mobile Device for the Automated Detection of Resting Tremor in Parkinson’s Disease and Essential Tremor

“…In other previous studies [ 10 , 11 , 12 , 13 , 14 ], mobile applications on Apple iPhone for the analysis of tremor in patients with PD and ET, performing accelerometer measurements, were tested, suggesting that those apps were a valid alternative tool to EMG in assessing the frequency of tremor. Other authors investigated the evaluation of tremor severity in PD using wearable inertial devices [ 15 , 16 ]; in particular, López-Blanco et al [ 17 ] focused on rest tremor.…”