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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6363699/ https://www.ncbi.nlm.nih.gov/pubmed/30761078 http://dx.doi.org/10.3389/fneur.2019.00048 |
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author | Varghese, Julian Niewöhner, Stephan Soto-Rey, Iñaki Schipmann-Miletić, Stephanie Warneke, Nils Warnecke, Tobias Dugas, Martin |
author_facet | Varghese, Julian Niewöhner, Stephan Soto-Rey, Iñaki Schipmann-Miletić, Stephanie Warneke, Nils Warnecke, Tobias Dugas, Martin |
author_sort | Varghese, Julian |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6363699 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-63636992019-02-13 A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders Varghese, Julian Niewöhner, Stephan Soto-Rey, Iñaki Schipmann-Miletić, Stephanie Warneke, Nils Warnecke, Tobias Dugas, Martin Front Neurol Neurology 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. Frontiers Media S.A. 2019-01-30 /pmc/articles/PMC6363699/ /pubmed/30761078 http://dx.doi.org/10.3389/fneur.2019.00048 Text en Copyright © 2019 Varghese, Niewöhner, Soto-Rey, Schipmann-Miletić, Warneke, Warnecke and Dugas. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Varghese, Julian Niewöhner, Stephan Soto-Rey, Iñaki Schipmann-Miletić, Stephanie Warneke, Nils Warnecke, Tobias Dugas, Martin A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders |
title | A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders |
title_full | A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders |
title_fullStr | A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders |
title_full_unstemmed | A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders |
title_short | A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders |
title_sort | smart device system to identify new phenotypical characteristics in movement disorders |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6363699/ https://www.ncbi.nlm.nih.gov/pubmed/30761078 http://dx.doi.org/10.3389/fneur.2019.00048 |
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