Study of Locomotor Expectations for Ascending/descending Slope and Stairs in Patients with Limb Amputations

Recruiting

• Conditions: Lower Limb Amputation
• Interventions: Other: 3D analysis of walking and balance; Other: Functional analyses

• Registration Number: NCT04030650
• Lead Sponsor: Centre Hospitalier Universitaire Dijon

Brief Summary

Patients with lower limb amputations are equipped with prostheses that can be mechanical and/or electronic. These prostheses can be mono-articular (only the ankle) or bi-articular (knee and ankle for example). For amputee patients, situations that may seem trivial, such as climbing and descending stairs, become complex. Thus during the descent of stairs, an unamputated person will slow down the descent by contracting the thigh muscles, which are obviously lacking in the amputee patient. Current prostheses, known as "intelligent" (or "microprocessor") prostheses, make it possible to adjust the locomotion only once the first step has been taken and to assist the patient during ascent/descent situations on slopes and stairs. The next technological challenge in the development of lower limb equipment is to be able to anticipate these complex environmental situations, in order to secure and facilitate movement even before the obstacle is crossed or the terrain changed.

This project plans to use the locomotor expectations commonly made during walking as a means of regulating the locomotor pattern. We believe that these expectations will depend on the situation, i.e. a particular anticipation when climbing or descending a slope, or when approaching a staircase, etc. To understand and describe these locomotor expectations, we plan to use recent techniques called supervised machine learning. These will make it possible to classify locomotor behaviour when walking on a slope or stairs. In the second phase, we would like to describe precisely the characteristics of the movements of the joints, and of the muscles during these adaptations. The final objective of this work is to create an autonomous sensor system to control the anticipatory behaviour of a lower limb prosthesis.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2019-07-22
• Study First Submitted QC: 2019-07-22
• Study First Posted: 2019-07-24
• Study Start: 2019-09-20
• Status Verified: 2024-10
• Last Update Submitted: 2024-10-15
• Last Update Posted: 2024-10-16
• Primary Completion: 2026-05
• Study Completion: 2026-05

Recruitment & Eligibility

• Status: RECRUITING
• Sex: All
• Target Recruitment: 70

Inclusion Criteria

Healthy volunteers:

• person who has given oral consent
• male or female adult
• person being able to understand simple orders, locomotion instructions

Lower limb amputee patients:

• person who has given oral consent
• male or female adult
• patient with unilateral major lower limb amputation of any origin (traumatic, vascular, infectious, congenital or neoplastic) with definitive equipment used routinely for at least 3 months.
• person able to understand simple orders, locomotion instructions

Exclusion Criteria

• person not affiliated or not benefiting from a heath insurance system
• person subject to a legal protection measure (curatorship, guardianship)
• person with a legal guardian
• pregnant or breastfeeding woman
• adult unable to consent
• person with a dislocated hip
• subject with conditions or disabilities other than amputation that affect walking

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
healthy volunteers	3D analysis of walking and balance	-
patients	Functional analyses	patients with lower limb amputations
healthy volunteers	Functional analyses	-
patients	3D analysis of walking and balance	patients with lower limb amputations

Primary Outcome Measures

Name	Time	Method
The error rate of the algorithm	2 months	The error rate of the algorithm for predicting the situation encountered in the next step

Trial Locations

Locations (1)

CHU Dijon Bourgogne; 🇫🇷 Dijon, France