Clinical trial Recruiting at 1 site Interventional Ages 18 to 65

Evaluation of a new prosthesis for upper limb amputation control

Official title: Clinical Evaluation of Intuitive, Bidirectional Strategies for the Control of Multi-articulated Prostheses for Upper Limb Amputation

Run by Scuola Superiore di Studi Universitari e di Perfezionamento Sant'Anna · NCT06886295 · Data updated 2026-11-12

This study is testing a new type of upper limb prosthesis that uses machine learning to help people with amputations move more naturally and feel better about using it compared to the usual control methods.

Quick facts

Study typeInterventional
Ages18 Years to 65 Years
SexAll
Enrollment14 (estimated)
SponsorScuola Superiore di Studi Universitari e di Perfezionamento Sant'Anna
Academic / other
Locations1 site (Bologna, Bo)
StatusRecruiting
StartedApril 1, 2025
Main results expectedDecember 31, 2026
Study endsDecember 31, 2026
Registry record updatedApril 3, 2025
Trial IDNCT06886295 on ClinicalTrials.gov

Is this trial a fit for you?

Likely a good fit

Ideal candidates for this study are individuals with transradial amputation who have some experience using myoelectric prostheses.

Probably not a fit

Patients with significant cognitive deficits, severe comorbidities, or those who cannot understand the Italian language may not benefit from this study.

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This study aims to validate a non-invasive upper limb prosthesis that utilizes machine learning for intuitive movement control based on myoelectric signals, combined with vibrotactile feedback for enhanced user experience. The pilot study employs a randomized crossover design to compare this innovative control strategy against the standard direct control method. Participants will use the prosthesis in their daily lives over several weeks, allowing for assessment of dexterity, motor coordination, and user satisfaction through functional tests and questionnaires.

Why it matters

Potential benefit: If successful, this prosthesis could significantly improve the quality of life for individuals with upper limb amputations by providing more intuitive control and sensory feedback.

How similar studies have gone: While the approach of integrating machine learning and sensory feedback in prosthetics is innovative, similar studies have shown promise in enhancing prosthetic control and user satisfaction.

Who can join: the full rules

Show full inclusion / exclusion criteria
Inclusion Criteria:

* subjects with transradial amputation, and minimum experience in the use of myoelectric prosthesis;
* subjects who have expressed informed consent to participate in the study and consent to data processing.

Exclusion Criteria:

* subjects with obvious visual and oculomotor defects;
* concomitant comorbidities/disabilities/chronic conditions, general or localized (Multiple Sclerosis, Parkinson's disease, muscle tone disorders, malignant neoplasms, etc.), which may interfere with the performance of the study;
* pregnancy or breastfeeding;
* declared or evident cognitive deficits that compromise the understanding of the required tasks (mini Mental State Examination≤ 24);
* difficulty in understanding the Italian language.

Where it's running

  • IRCCS Istituto Ortopedico Rizzoli
    Bologna, Bo, Italy
    Recruiting

Study contacts

Similar studies

Other studies for the same condition or treatment. Recruiting studies are listed first.

How to take part

  1. Review the eligibility criteria above with your treating physician.
  2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
  3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.
Last reviewed 2026-11-14 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.