Utilizing Smart Devices to Identify New Phenotypical Characteristics in Movement Disorders

NCT ID: NCT03638479

Last Updated: 2022-06-13

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Total Enrollment

513 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-01-08

Study Completion Date

2021-12-31

Brief Summary

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This observational and experimental study seeks to establish a Smart Device System (SDS) to monitor high-resolution handtremor-based data using Smartphones, SmartWatches and Tablets. By doing this, movement data will be analyzed in depth with advanced statistical and Deep-Learning algorithms to identify new clinical phenotypical characteristics Parkinson's Disease and Essential Tremor.

Detailed Description

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Current smart devices as smartphones and smartwatches have reached a level of technical sophistication that enables high-resolution monitoring of movements not only for everyday sports activities but also for movement disorders. Tremor-related diseases as Parkinson's Disease (PD) and Essential Tremor (ET) are two of the most common movement disorders. Disease classification is primarily based on clinical criteria and remains challenging. The primary goal of this study is to identify new phenotypical characteristics based on the captured movement data by the tremor-capturing smartwatches and tablets and smartphone-based questionnaires.

The system will be applied and analyzed within an experimental and observational setting and only captures from patients, which have received informed consent. Within the study period, the SDS is not intended as clinical diagnostic support for physicians and will be not be used as medical device.

Conditions

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Parkinson Disease Essential Tremor Movement Disorders Parkinson's Syndrome Atypical Parkinsonism

Study Design

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Observational Model Type

CASE_CONTROL

Study Time Perspective

PROSPECTIVE

Study Groups

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Parkinson's Disease

Participant's diagnosed with Parkinson's Disease

Data Capture

Intervention Type OTHER

This is no intervention. Participants of all groups will receive data Capture with smartphones, smartwatches and tablets.

Essential Tremor

Participant's diagnosed with Essential Tremor or other Movement Disorders

Data Capture

Intervention Type OTHER

This is no intervention. Participants of all groups will receive data Capture with smartphones, smartwatches and tablets.

No Parkinson's Disease and No Essential Tremor

Participant's with no diagnosis of PD, ET or other Movement Disorders

Data Capture

Intervention Type OTHER

This is no intervention. Participants of all groups will receive data Capture with smartphones, smartwatches and tablets.

Interventions

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Data Capture

This is no intervention. Participants of all groups will receive data Capture with smartphones, smartwatches and tablets.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Diagnosed with Parkinson's Disease (ICD-10-GM G20.-) or Essential Tremor (G25.0)
* Comparison group: Other movement disorders including atypical Parkinsonian disorders and healthy participants

Exclusion Criteria

* Unable to obtain informed consent
* Skin-related conditions at one of the wrists or any other medical conditions that could harm the participant's health by wearing the smartwatch at both wrists.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Universität Münster

OTHER

Sponsor Role lead

Responsible Party

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Julian Varghese

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Julian Varghese, MD

Role: PRINCIPAL_INVESTIGATOR

WWU Münster, Institut für Medizinische Informatik

Locations

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Institute of Medical Informatics, University of Münster

Münster, , Germany

Site Status

Countries

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Germany

References

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Purk M, Fujarski M, Becker M, Warnecke T, Varghese J. Utilizing a tablet-based artificial intelligence system to assess movement disorders in a prospective study. Sci Rep. 2023 Jun 26;13(1):10362. doi: 10.1038/s41598-023-37388-3.

Reference Type DERIVED
PMID: 37365210 (View on PubMed)

Varghese J, Niewohner S, Soto-Rey I, Schipmann-Miletic S, Warneke N, Warnecke T, Dugas M. A Smart Device System to Identify New Phenotypical Characteristics in Movement Disorders. Front Neurol. 2019 Jan 30;10:48. doi: 10.3389/fneur.2019.00048. eCollection 2019.

Reference Type DERIVED
PMID: 30761078 (View on PubMed)

Other Identifiers

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VA111809

Identifier Type: -

Identifier Source: org_study_id

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