Handwriting Analysis in Movement Disorders (HANDWRML)

Advanced Machine Learning Analysis of Handwriting in Patients With Movement Disorders

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.

Study Overview

• Status: Recruiting
• Conditions: Parkinson Disease; Movement Disorders; Writing Disorder

• Study Type: Observational
• Enrollment (Anticipated): 40

Contacts and Locations

• Study Contact: Name: Antonio Suppa, MD; Phone Number: +00390649914074; Email: antonio.suppa@uniroma1.it

Study Locations

• Italy
  • Pozzilli, Italy, 86077
    • Recruiting
    • IRCCS Neuromed
    • Contact: Antonio Suppa, MD; Phone Number: +00390649914074

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 90 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Healthy subjects and patients with idiopathic PD

Description

Inclusion Criteria:

• Healthy conditions
• clinical diagnosis of Parkinson's disease

Exclusion Criteria:

• cognitive decline

Study Plan

How is the study designed?

Number of groups / cohorts

2

Cohorts and Interventions

Group / Cohort
Healthy Subjects; Collection of handwriting samples
Patients with Parkinson's disease; Collection of handwriting samples

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Stroke size of handwriting characters	height of single letters	through study completion, an average of 1 year

Collaborators and Investigators

• Sponsor: Neuromed IRCCS

Study record dates

Study Major Dates

• Study Start (Actual): December 1, 2022
• Primary Completion (Actual): December 31, 2022
• Study Completion (Anticipated): December 31, 2023

Study Registration Dates

• First Submitted: April 20, 2022
• First Submitted That Met QC Criteria: April 29, 2022
• First Posted (Actual): May 2, 2022

Study Record Updates

• Last Update Posted (Actual): March 23, 2023
• Last Update Submitted That Met QC Criteria: March 21, 2023
• Last Verified: March 1, 2023

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Parkinsonian Disorders; Basal Ganglia Diseases; Synucleinopathies; Neurodegenerative Diseases; Disease; Parkinson Disease; Movement Disorders
• Other Study ID Numbers: NEUR_04

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No