NCT05238389: iMotore

AI-based Upper Limb Rehabilitation Therapy With MOTORE

Completed NA Last updated 28 February 2024

What this trial tests

NA trial testing AI-based upper limb robotic therapy in Stroke in 44 participants. Completed in 30 March 2023.

Timeline

1 June 2022

Primary endpoint
30 March 2023

30 March 2023

Quick facts

Lead sponsor	Fondazione Don Carlo Gnocchi Onlus
Phase	NA
Status	Completed
Study type	INTERVENTIONAL
Allocation	na
Design	single group
Masking	none
Primary purpose	treatment
Enrollment	44
Start date	1 June 2022
Primary completion	30 March 2023
Estimated completion	30 March 2023
Sites	1 location across Italy

Drugs / interventions tested

• AI-based upper limb robotic therapy

Conditions studied

• Stroke — all drugs for Stroke →

Sponsor

Fondazione Don Carlo Gnocchi Onlus — full company profile →

Who can join

Adults 18 to 85, any sex, with Stroke. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

Stroke is a common disease with a high disabling impact; it is the world's second leading cause of death and the third leading cause of disability. Robotic therapy has been proposed as a viable approach for the rehabilitation of the upper limb, as a way to increase the amount and the intensity of the therapy, and to standardize the treatment. However, robotic technologies have not yet been used to their full potential in terms of tailoring rehabilitation paths and monitoring the response to treatments. The main goal of the study is to use AI algorithms to (a) predict the recovery of the patients and (b) suggest exercises and parameters to improve the outcomes of the treatment.

Publications & conference data

2 peer-reviewed publications reference this trial (live from Europe PMC):

1. Characteristics of Artificial Intelligence Clinical Trials in the Field of Healthcare: A Cross-Sectional Study on ClinicalTrials.gov.
   Wang A, Xiu X, Liu S, Qian Q, et al · · 2022 · cited 12× · PMID 36294269 · DOI 10.3390/ijerph192013691
2. Systematic data management for effective AI-driven decision support systems in robotic rehabilitation.
   Tzepkenlis A, Camardella C, Germanotta M, Aprile IG, et al · · 2025 · PMID 40739308 · DOI 10.1038/s41598-025-09740-2