Trial Outcomes & Findings for Exoskeleton Variability Optimization (NCT NCT04338815)

Last Updated: 2025-06-19

Results Overview

Convergence is determined when the estimated optimal exoskeleton settings vary less than 10%. The time to convergence is measured.

Recruitment status

TERMINATED

Study phase

Target enrollment

9 participants

Primary outcome timeframe

10 minutes

Results posted on

2025-06-19

Participant Flow

No enrolled participants were tested in the endurance arm because the preceding optimal assistance arm was not successful based on the convergence criteria.

Participant milestones

Participant milestones
Measure	Optimal Assistance Pattern An optimization algorithm will change the assistance pattern on the hip exoskeleton during walking sessions and the optimal assistance pattern will be determined when gait variability is minimized. Exoskeleton Optimization: Participants will walk 10-minute trials while an optimization algorithm changes the assistance profile of an exoskeleton.	Effects on Endurance The effects on endurance of participants using ground reaction force (Bertec treadmill), walking speed (Bertec treadmill), indirect calorimetry (Cosmed), and motion capture (Vicon) will be determined. Endurance Evaluation: Participants will walk 2 trials at a speed of 1 meter per second until the participant indicates claudication or a maximum duration of 6 minutes.
Overall Study STARTED	9	0
Overall Study COMPLETED	0	0
Overall Study NOT COMPLETED	9	0

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Exoskeleton Variability Optimization

Baseline characteristics by cohort

Baseline characteristics by cohort
Measure	Optimal Assistance Pattern n=9 Participants An optimization algorithm will change the assistance pattern on the hip exoskeleton during walking sessions and the optimal assistance pattern will be determined when gait variability is minimized. Exoskeleton Optimization: Participants will walk 10-minute trials while an optimization algorithm changes the assistance profile of an exoskeleton.	Effects on Endurance The effects on endurance of participants using ground reaction force (Bertec treadmill), walking speed (Bertec treadmill), indirect calorimetry (Cosmed), and motion capture (Vicon) will be determined. Endurance Evaluation: Participants will walk 2 trials at a speed of 1 meter per second until the participant indicates claudication or a maximum duration of 6 minutes.	Total n=9 Participants Total of all reporting groups
Age, Categorical <=18 years	0 Participants n=93 Participants	0 Participants n=4 Participants	0 Participants n=27 Participants
Age, Categorical Between 18 and 65 years	8 Participants n=93 Participants	0 Participants n=4 Participants	8 Participants n=27 Participants
Age, Categorical >=65 years	1 Participants n=93 Participants	0 Participants n=4 Participants	1 Participants n=27 Participants
Sex: Female, Male Female	4 Participants n=93 Participants	0 Participants n=4 Participants	4 Participants n=27 Participants
Sex: Female, Male Male	5 Participants n=93 Participants	0 Participants n=4 Participants	5 Participants n=27 Participants
Race (NIH/OMB) American Indian or Alaska Native	0 Participants n=93 Participants	0 Participants n=4 Participants	0 Participants n=27 Participants
Race (NIH/OMB) Asian	2 Participants n=93 Participants	0 Participants n=4 Participants	2 Participants n=27 Participants
Race (NIH/OMB) Native Hawaiian or Other Pacific Islander	0 Participants n=93 Participants	0 Participants n=4 Participants	0 Participants n=27 Participants
Race (NIH/OMB) Black or African American	1 Participants n=93 Participants	0 Participants n=4 Participants	1 Participants n=27 Participants
Race (NIH/OMB) White	5 Participants n=93 Participants	0 Participants n=4 Participants	5 Participants n=27 Participants
Race (NIH/OMB) More than one race	0 Participants n=93 Participants	0 Participants n=4 Participants	0 Participants n=27 Participants
Race (NIH/OMB) Unknown or Not Reported	1 Participants n=93 Participants	0 Participants n=4 Participants	1 Participants n=27 Participants
Region of Enrollment United States	9 participants n=93 Participants	—	9 participants n=27 Participants

PRIMARY outcome

Timeframe: 10 minutes

Population: The time to convergence for the optimal assistance pattern could not be reported since the convergence criterion was not achieved. The effect on endurance arm was not analyzed since the preceding optimal assistance pattern aim was not successful based on the predefined convergence criteria.

Convergence is determined when the estimated optimal exoskeleton settings vary less than 10%. The time to convergence is measured.

Outcome measures

Outcome data not reported

PRIMARY outcome

Timeframe: 20 seconds

Population: The effect on endurance arm was not analyzed since the preceding optimal assistance pattern aim was not successful based on the predefined convergence criteria.

The time to peak extension moment of exoskeleton is measured by plotting the exoskeleton moment versus stride cycle percentage and finding the timing when the peak in the extension moment occurs expressed in percent of the stride cycle.

Outcome measures

Outcome measures
Measure	Optimal Assistance Pattern n=9 Participants An optimization algorithm will change the assistance pattern on the hip exoskeleton during walking sessions and the optimal assistance pattern will be determined when gait variability is minimized. Exoskeleton Optimization: Participants will walk 10-minute trials while an optimization algorithm changes the assistance profile of the exoskeleton.	Endurance Effectds The effects on endurance of participants using ground reaction force (Bertec treadmill), walking speed (Bertec treadmill), indirect calorimetry (Cosmed), and motion capture (Vicon) will be determined. Endurance Evaluation: Participants will walk 2 trials at a speed of 1 meter per second until the participant indicates claudication or a maximum duration of 6 minutes.
Peak Extension Timing	86 % stride cycle Standard Deviation 8	—

PRIMARY outcome

Timeframe: 20 seconds

Population: The effect on endurance arm was not analyzed since the preceding optimal assistance pattern aim was not successful based on the predefined convergence criteria.

The time to peak flexion moment of exoskeleton is measured by plotting the flexion moment versus stride cycle percentage and finding the timing when the peak in the flexion moment occurs expressed in percent of the stride cycle.

Outcome measures

Outcome measures
Measure	Optimal Assistance Pattern n=9 Participants An optimization algorithm will change the assistance pattern on the hip exoskeleton during walking sessions and the optimal assistance pattern will be determined when gait variability is minimized. Exoskeleton Optimization: Participants will walk 10-minute trials while an optimization algorithm changes the assistance profile of the exoskeleton.	Endurance Effectds The effects on endurance of participants using ground reaction force (Bertec treadmill), walking speed (Bertec treadmill), indirect calorimetry (Cosmed), and motion capture (Vicon) will be determined. Endurance Evaluation: Participants will walk 2 trials at a speed of 1 meter per second until the participant indicates claudication or a maximum duration of 6 minutes.
Peak Flexion Timing	56 % stride cycle Standard Deviation 2	—

PRIMARY outcome

Timeframe: 20 seconds

Population: The effect on endurance arm was not analyzed since the preceding optimal assistance pattern aim was not successful based on the predefined convergence criteria.

Largest Lyapunov exponent (the rate of separation of infinitesimally close trajectories) of lower limb kinematics is determined. Largest Lyapunov exponent is calculated using Wolf's algorithm. The theoretical range is from zero to plus infinity. Zero indicates an entirely stable periodic movement pattern. Higher values indicate more unstable and chaotic movement patterns. Lower values are considered better, and higher values are considered worse for gait stability.

Outcome measures

Outcome measures
Measure	Optimal Assistance Pattern n=9 Participants An optimization algorithm will change the assistance pattern on the hip exoskeleton during walking sessions and the optimal assistance pattern will be determined when gait variability is minimized. Exoskeleton Optimization: Participants will walk 10-minute trials while an optimization algorithm changes the assistance profile of the exoskeleton.	Endurance Effectds The effects on endurance of participants using ground reaction force (Bertec treadmill), walking speed (Bertec treadmill), indirect calorimetry (Cosmed), and motion capture (Vicon) will be determined. Endurance Evaluation: Participants will walk 2 trials at a speed of 1 meter per second until the participant indicates claudication or a maximum duration of 6 minutes.
Largest Lyapunov Exponent	6.6 (Lyapunov exponent is unitless) Standard Deviation 2.8	—

Adverse Events

Optimal Assistance Pattern

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Effects on Endurance

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Adverse event data not reported

Additional Information

Philippe Malcolm

University of Nebraska-Omaha

Phone: 617-487-1148

Email: [email protected]

Results disclosure agreements

Principal investigator is a sponsor employee
Publication restrictions are in place