[The new tremor classification of the International Parkinson and Movement Disorder Society : Update on frequent tremors]

Mobile Applications for Resting Tremor Assessment in Parkinson’s Disease: A Systematic Review

(1) Background: Resting tremor is a motor manifestation present in most Parkinson’s disease (PD) patients. For its assessment, several scales have been created, but mobile applications could help in objectively assessing resting tremor in PD patients in person and/or remotely in a more ecological scenario. (2) Methods: a systematic review following the PRISMA recommendations was conducted in scientific databases (PubMed, Medline, Science Direct, Academic Search Premier, and Web of Science) and in the main mobile application markets (Google Play, iOS App Store, and Windows Store) to determine the applications available for the assessment of resting tremor in patients with PD using only the measurement components of the phone itself (accelerometers and gyroscopes). (3) Results: 14 articles that used mobile apps to assess resting tremor in PD were included, and 13 apps were identified in the mobile application markets for the same purpose. The risk of bias and of applicability concerns of the articles analyzed was low. Mobile applications found in the app markets met an average of 85.09% of the recommendations for the development of medical mobile applications. (4) Conclusions: the use of mobile applications for the evaluation of resting tremor in PD patients has great potential, but validation studies for this purpose are scarce.

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

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.