Adaptive Recalibration of Prosthetic Leg Neural Control System

The purpose of this study is for transfemoral amputees to walk with an experimental robotic prosthesis. Electric signals will be measured from their muscles and used to help control an artificial leg. The investigators will record from sensors placed on a prosthesis and electric signals measured from muscles in the participants leg to see if the investigators can develop better computer programs to help predict subject actions and prostheses function.

Completed

Looking for future studies?

Notify Me

Key information

Conditions

Amputation

Age range

18 year–80 year

Sex eligibility

All sexes

Study type

Interventional

Phase

Not applicable

Primary location

Rehabilitation Institute of Chicago

Chicago, Illinois, 60611, United States

About this study

The investigators propose to use a powered knee-ankle prosthesis that is not yet commercially available. The hierarchical control framework the investigators are developing will be equally applicable to any prosthetic leg that needs to be transitioned between ambulation modes, including microprocessor-controlled passive devices.

The overall objective is to develop and evaluate an adaptive framework for controlling lower limb prostheses that compensates for changes in EMG signals. When a participant walks on a lower limb prosthesis, the output of the high-level controller (or ambulation mode predictor) directly influences patterns generated by the participant. After the participant has completed the subsequent stride, a gait pattern estimator (GPE), will provide a label of what the participant actually did. This may differ from the ambulation mode predictor output if there was a misclassification. The label will then be used to update the ambulation mode predictor algorithm such that future steps are predicted with higher accuracies. Finally, the resulting system will be transferred to an embedded system and tested in real-time with transfemoral amputees and compared to a non-adaptive system.

Who can participate

Healthy volunteers accepted: Yes

Only the study team can determine whether someone qualifies for participation.

Amputee Subjects

Inclusion criteria

Lower Limb Amputees
K2/K3/K4 ambulators

Exclusion criteria

Over 250lbs body weight
Inactive, physically unfit
cognitive deficits or visual impairment that would impair their ability to give informed consent or to follow simple instructions during the experiments
Pregnant women
co-morbidity that interferes with the study (e.g. stroke, pace maker placement, severe ischemia cardiac disease, etc.)

Able-bodied Subjects:

Inclusion criteria

no injury on either lower extremity

Exclusion criteria

inactive, physically unfit
over 250 lbs body weight
cognitive deficits or visual impairment that would impair their ability to give informed consent or impair their ability to follow simple instructions during the experiments
Pregnant women (status determined by self-reporting)
co-morbidity that interferes with the study (e.g. stroke, pace maker placement, severe ischemia cardiac disease, etc.)

Treatment and study plan

Powered knee and ankle prosthesis

Device

A powered knee and ankle prosthesis developed by Vanderbilt University.

Primary outcomes

Decreased error rates for pattern recognition system used to predict ambulation modes

Time frame: Assessed at approximately 2 months and 6 months after enrollment

Pattern recognition algorithms have been used to allow seamless and automatic transitioning between ambulation modes. Classification errors result in the prosthesis predicting the wrong ambulation mode. A decrease in errors results in improved mode prediction by the prosthesis. EMG from the participant and mechanical sensor data from the prosthesis are processed with the use of a phase-based-dependent pattern recognition classification method. The data collection will yield three groups of 10 real-time trials. The investigators primary analysis will be a repeated measures ANOVA with a planned contrast between the groups. The investigators will also complete a secondary analysis using the data collected while the participants ambulated outside of the laboratory. The total number of misclassifications will be computed. This will allow the investigator to evaluate the rate at which the overall classification system adapted.

Sponsors and collaborators

Lead sponsor

Shirley Ryan AbilityLab

Other

Registry information

Important dates

Study start: 2015
Primary completion: 2020
Study completion: 2020
First posted: Feb 4, 2015
Registry last updated: Oct 28, 2020

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

Published trials that share one or more normalized conditions with this study.

Completed