Towards Efficient Personalization of Computerized Lower Limb Prostheses Via Reinforcement Learning in a Clinical Setup - Group 1

NCT07204925 | Recruiting Phase 1 FDA Device

• 2 other identifiers: 28186U.S. NIH 1R01HD116422-01A1
• Study Type: interventional
• Target: 24
• Locations: 1 country
• Sites: 1

Brief Summary

The goal of this clinical trial is to understand the feasibility and effectiveness of using reinforcement learning to personalize robotic prosthetic legs (an experimental prototype) for unilateral transfemoral amputees. The main questions it aims to answer are:

• With the developed RL-based Recommendation Interfacing System (RISE), clinicians are able to personalize prosthetic legs faster compared with existing manual personalization procedures.
• With the developed RL-based Recommendation Interfacing System (RISE), clinicians are able to personalize prosthetic legs without detailed knowledge about how the prosthetic legs are controlled.
• Patients perform better when the prosthetic legs are personalized with RISE system compared with the ones personalized manually Researchers will compare two arms (RISE guided personalization and manual personalization) to see if the tuning speed will increase and if patients can perform better. Participants will go through the standard prosthetic fitting procedures, such as alignment adjustment, then they will experience repeated prosthesis personalization procedures conducted by tuning specialists without RISE, tuning specialists with RISE, and prosthetists (without tuning expertise) with RISE on different types of terrains. In the end, the participants will go through a testing trial, in which they will experience the prototype personalized through the three different approaches without knowing how the control parameters are decided. Their walking performance will be recorded. It is expected that the participants will visit the testing site 8 times, which including alignment (1 visit), three personalization procedures (twice for each), and one testing trial (1-2 visits).

Conditions

Transfemoral Amputation

Keywords

Powered prosthesis legs; control parameter personalization; reinforcement learning

Outcome Measures

Primary Outcomes (1)

• Total personalization time

  Time needed to finish the personalization of the prosthetic leg

  During the visit arranged for personalization

Secondary Outcomes (3)

• Walking speed

  During the last visit for evaluation

• Step length

  During the last visit for evaluation

• foot elevation

  during the last visit for evaluation

Study Arms (3)

Tuning expert without RISE

ACTIVE COMPARATOR

Tuning experts decide the control parameters based on their knowledge about the powered prosthetic device and patients' feedback

Device: Manual personalization of the prosthetic leg by tuning experts

Tuning expert with RISE

ACTIVE COMPARATOR

The control parameters of the prosthetic legs are decided by tuning experts with the help of the developed RISE system

Device: RISE guided personalization of prosthetic legs by tuning experts

Prosthetists with RISE

ACTIVE COMPARATOR

Control parameters of the prosthetic leg are decided by prosthetists, who are not familiar with the prosthetic leg prototype, with the RISE system.

Device: RISE guided personalization of prosthetic legs by prosthetists

Interventions

RISE guided personalization of prosthetic legs by tuning experts DEVICE

The personalization procedure is conducted by tuning experts based on the recommendation of RISE system

Tuning expert with RISE

RISE guided personalization of prosthetic legs by prosthetists DEVICE

The control parameters of the prosthetic leg prototype is decided by prosthetists without detailed knowledge about the prosthetic leg with the help of developed RISE system

Prosthetists with RISE

Manual personalization of the prosthetic leg by tuning experts DEVICE

The control parameters of the prosthetic legs are decided by tuning experts based on their knowledge of the prosthetic leg prototypes and patients' response.

Tuning expert without RISE

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Unilateral transfemoral amputees between 18-75 with K level three or higher
• More than one year after amputation
• Using current prosthetic socket and leg for more than three months
• No major skin issues on the residual limb for more than six months
• Can walk for more than 4 minutes continuously without any other assistive devices

You may not qualify if:

• Have very short residual thighs (the length of the residual limb is \<15% of the length of the unimpaired limb)
• Are \<1.50m in height or \>116Kg in weight (who would not fit our prosthesis or the PowerKnee)
• Have cognitive, visual, audio impairments that would affect their ability to give informed consent or to follow simple Instructions during the experiments
• Have any significant co-morbidity that interferes with the study (e.g. stroke, pacemaker placement, pain, etc.).

Sponsors & Collaborators

• North Carolina State University: lead
• Arizona State University: collaborator
• University of North Carolina, Chapel Hill: collaborator

Study Sites (1)

North Carolina State University

Raleigh, North Carolina, 27695, United States

RECRUITING

Study Officials

• He (Helen) Huang, PhD

  NC State University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Ming Liu, PhD

CONTACT

9195158541; mliu10@ncsu.edu

Laura Rohrbaugh, BS

CONTACT

919-513-3840; lasmith6@ncsu.edu

Study Design

• Study Type: interventional
• Phase: phase 1
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, OUTCOMES ASSESSOR
• Masking Details: During the evaluation trial, the participants and evaluators are blinded on how the personalized parameters are decided.
• Purpose: DEVICE FEASIBILITY
• Intervention Model: CROSSOVER
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: September 2, 2025
• First Posted: October 2, 2025
• Study Start: August 1, 2025
• Primary Completion (Estimated): July 31, 2031
• Study Completion (Estimated): October 30, 2031
• Last Updated: October 2, 2025

Record last verified: 2025-09

Data Sharing

• IPD Sharing: Will not share

Locations

US (1)