Handwriting Analysis in Movement Disorders

NCT ID: NCT05355480

Last Updated: 2023-03-23

Basic Information

• Recruitment Status: UNKNOWN
• Total Enrollment: 40 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2022-12-01
• Study Completion Date: 2023-12-31

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.

Conditions

Movement Disorders; Parkinson Disease; Writing Disorder

Study Design

• Observational Model Type: CASE_CONTROL
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

Healthy Subjects

Collection of handwriting samples

No interventions assigned to this group

Patients with Parkinson's disease

Collection of handwriting samples

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• Healthy conditions
• clinical diagnosis of Parkinson's disease

Exclusion Criteria

• cognitive decline

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 90 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Neuromed IRCCS

OTHER

Sponsor Role: lead

Responsible Party

Antonio Suppa

Prof.

Responsibility Role: PRINCIPAL_INVESTIGATOR

Locations

IRCCS Neuromed

Pozzilli, , Italy

Site Status: RECRUITING

Countries

Italy

Central Contacts

Antonio Suppa, MD

Role: CONTACT

antonio.suppa@uniroma1.it

+00390649914074

Facility Contacts

Antonio Suppa, MD

Role: primary

+00390649914074

Other Identifiers

NEUR_04

Identifier Type: -

Identifier Source: org_study_id