Improving Balance and Energetics of Walking Using a Hip Exoskeleton
Public ClinicalTrials.gov record NCT05447884. Field values are reproduced from the official study page; the official ClinicalTrials.gov record remains the source of truth for eligibility, enrollment, and contact information.
Data is sourced from official ClinicalTrials.gov public API records. Always review the official ClinicalTrials.gov record for the latest information.
Official title
Learning-based Control of a Hip Exoskeleton to Improve Balance and Energetics of Human Walking Functions
Brief summary
Reproduced verbatim from the official ClinicalTrials.gov record. Not medical advice.
Robotic lower limb exoskeletons aim to improve or augment limb functions. Automatic modulation of robotic assistance is very important because it can increase the assistive outcomes and guarantee safety when using exoskeletons. However, this automatic assistance adjustment is challenging due to person-to-person and day-to-day variations, as well as the time-varying complex human-machine-interaction forces. In recent years, human-in-the-loop optimization methods have been investigated to reduce participants' metabolic costs by providing personalized assistance from robotic exoskeletons. However, metabolic cost measure is noisy and the experimental protocol is usually relatively long. In addition, the influence of exoskeleton control on this human state in terms of energetic cost is unclear and indirect. More importantly, the optimization by reducing metabolic cost is found to affect human gait patterns and cause undesired outcomes. In this study, new evaluation measures other than metabolic cost will be investigated to optimize the assistance from a powered hip exoskeleton based on a reinforcement learning method. It is hypothesized that the new reinforcement learning-based optimal control approach will produce personalized torque assistance, reduce human volitional effort, and improve balance and other performance during walking tasks. Both participants without and with neurological disorders will be included in this study.
Study identification
- NCT ID
- NCT05447884
- Recruitment status
- Not listed
- Study type
- Interventional
- Phase
- Not applicable
- Enrollment
- 100 participants
Conditions and interventions
Eligibility (public fields only)
- Age range
- 18 Years to 64 Years
- Sex
- All
- Healthy volunteers
- Accepts healthy volunteers
This page does not interpret eligibility. Detailed inclusion and exclusion criteria are on the official ClinicalTrials.gov record.
Study timeline
- Start date
- May 31, 2022
- Primary completion
- Dec 30, 2024
- Completion
- Dec 30, 2025
- Last update posted
- Dec 19, 2023
2022 – 2025
United States locations
- U.S. sites
- 1
- U.S. states
- 1
- U.S. cities
- 1
| Facility | City | State | ZIP | Site status |
|---|---|---|---|---|
| North Carolina State University | Raleigh | North Carolina | 27695 | Recruiting |
Site contact phone numbers, emails, and investigator names are intentionally not displayed here. Open the official ClinicalTrials.gov record for site contact information.
About this trial record page
- What this page shows
- Public field values for ClinicalTrials.gov record NCT05447884, including study identification, conditions, interventions, eligibility (age, sex, healthy volunteer), timeline, and U.S. site list.
- What this page does not do
- No medical advice, eligibility judgments, treatment recommendations, study quality scoring, or AI-generated medical summaries. No site contact phone numbers, emails, or investigator names.
- Where the data comes from
- Sourced from the official ClinicalTrials.gov public API. The official record is the source of truth.
- Last refresh
- Last update posted Dec 19, 2023 · Synced Sep 4, 2026
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Open the official record
The complete protocol, eligibility criteria, and contact information for NCT05447884 live on ClinicalTrials.gov.