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HANDWRML: Handwriting Analysis in Movement Disorders

Sponsor
Neuromed IRCCS (Other)
Overall Status
Not yet recruiting
CT.gov ID
NCT05355480
Collaborator
(none)
40
Enrollment
19
Anticipated Duration (Months)

Study Details

Study Description

Brief Summary

Handwriting is a complex cognitive prowess that deteriorates in patients affected by neurodegenerative diseases, including movement disorders. More in detail, patients with Parkinson's disease (PD) may manifest prominent handwriting abnormalities which have been collectively identified as parkinsonian micrographia. MIcrographia may manifest at the onset of the disease and then worsens progressively with time. Previous techniques released to investigate micrographia in PD relied on perceptual analysis of simple tasks or were based on expensive technological tools, including tablets. However, handwriting can be promptly collected in an ecological scenario, through safe, cheap, and largely available tools. Also, the objective handwriting analysis through artificial intelligence would represent an innovative strategy even superior to previous techniques, since it allows for the analysis of large amounts of data. In this experimental project, the investigators apply a specific machine learning algorithm to analyze handwriting samples recorded in healthy controls and PD patients. The study aims to verify whether the technique proposed by the investigators would be able to detect parkinsonian micrographia objectively, monitor the evolution of handwriting abnormalities and assess the symptomatic improvement of handwriting following L-Dopa administration in PD patients.

Condition or Disease Intervention/Treatment Phase

    Study Design

    Study Type:
    Observational
    Anticipated Enrollment :
    40 participants
    Observational Model:
    Case-Control
    Time Perspective:
    Cross-Sectional
    Official Title:
    Advanced Machine Learning Analysis of Handwriting in Patients With Movement Disorders
    Anticipated Study Start Date :
    Jun 1, 2022
    Anticipated Primary Completion Date :
    Dec 31, 2022
    Anticipated Study Completion Date :
    Dec 31, 2023

    Arms and Interventions

    Arm Intervention/Treatment
    Healthy Subjects

    Collection of handwriting samples
    Patients with Parkinson's disease

    Collection of handwriting samples

    Outcome Measures

    Primary Outcome Measures

    1. Stroke size of handwriting characters [through study completion, an average of 1 year]

      height of single letters

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    18 Years to 90 Years
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    Yes
    Inclusion Criteria:

    • Healthy conditions

    • clinical diagnosis of Parkinson's disease

    Exclusion Criteria:
    • cognitive decline

    Contacts and Locations

    Locations

    No locations specified.

    Sponsors and Collaborators

    • Neuromed IRCCS

    Investigators

    None specified.

    Study Documents (Full-Text)

    None provided.

    More Information

    Publications

    None provided.
    Responsible Party:
    Antonio Suppa, Prof., Neuromed IRCCS
    ClinicalTrials.gov Identifier:
    NCT05355480
    Other Study ID Numbers:
    • NEUR_04
    First Posted:
    May 2, 2022
    Last Update Posted:
    May 2, 2022
    Last Verified:
    Apr 1, 2022
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Additional relevant MeSH terms:
    Parkinson Disease
    Movement Disorders
    Disease

    Study Results

    No Results Posted as of May 2, 2022