Movement Disorders Analysis Using a Deep Learning Approach

NCT ID: NCT04974034

Last Updated: 2021-07-23

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

50 participants

Study Classification

OBSERVATIONAL

Study Start Date

2019-06-01

Study Completion Date

2020-12-31

Brief Summary

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Bradykinesia is a key parkinsonian feature yet subjectively assessed by the MDS-UPDRS score, making reproducible measurements and follow-up challenging.

In a Movement Disorder Unit, the investigators acquired a large database of videos showing parkinsonian patients performing Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III protocols.

Using a Deep Learning approach on these videos, the investigators aimed to develop a tool to compute an objective score of bradykinesia from the three upper limb tests described in the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III.

Detailed Description

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Conditions

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Bradykinesia Parkinson Disease Hypokinesia Akinesia Parkinsonian Syndrome Parkinsonian Disorders

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Age \> 18 years

Exclusion Criteria

* Refusal of participation
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Hospital Avicenne

OTHER

Sponsor Role lead

Responsible Party

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Desjardins Clement

Neurology Resident

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Clément Desjardins, MD

Role: PRINCIPAL_INVESTIGATOR

Hospital Avicenne

Bertrand Degos, MD,PhD

Role: STUDY_DIRECTOR

Hospital Avicenne

Locations

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Hospital Avicenne

Bobigny, Seine Saint Denis, France

Site Status

Countries

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France

Other Identifiers

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CLEA-2019-83

Identifier Type: -

Identifier Source: org_study_id

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