Improving Balance and Energetics of Walking Using a Hip Exoskeleton
Learning-based Control of a Hip Exoskeleton to Improve Balance and Energetics of Human Walking Functions
Who can join
Ages 18 to 64 · All sexes · Healthy volunteers welcome
Full eligibility criteria
Inclusion Criteria for non-neurologically affected populations: * Between 18 and 64 years old * Live in the United States * Able to understand study requirements and sign an informed consent * Have full range of motion in your hip joint * Able to walk normally without any assistance. Exclusion Criteria for non-neurologically affected populations: * Cannot follow instructions or provide feedback due to cognitive or language limitations * Suffered from a stroke that affects balance or walking * Use an electronically controlled medical device, such as a pacemaker, implanted defibrillator, or drug pump * Pregnancy * Experience numbness, tingling, muscle weakness, pain, or paralysis in any part of your body * Cannot walk or balance without help from a person or a tool, such as a walker or cane * Limited movement in your hip or ankle * You have any skin-related allergies or irritation to adhesives * Have blood circulation, heart, metabolic, or cognitive disorders, including but not limited to: Peripheral vascular disease, Pitting edema, Heart disease, Diabetes (uncontrolled), Seizures, and Cognitive diagnoses that affect their ability to process information. Inclusion Criteria for subjects who suffered a stroke: * Between 18 and 64 years old * Live in the United States * Able to understand study requirements and sign an informed consent * Have weakness on one side of their body due to a stroke within the past 6 months * Have the doctor confirm that the subjects had a stroke within the past 6 months * Can walk without any assistance for at least 6 minutes and 1000 feet (a little less than a quarter-mile) * Can walk at a speed of 1 mile per hour * Have normal or corrected-to-normal vision and hearing * Capable of safely stepping on stairs without an Ankle-Foot Orthosis but may use canes as needed Exclusion Criteria for subjects who suffered a stroke: * Cannot follow instructions or provide feedback due to cognitive, spatial awareness, and/or language limitations * Are pregnant * Cannot walk without an ankle-foot brace or a therapist's assistance * Cannot walk or balance without the help of a tool, such as a walker or cane * Have vision, balance, or reaching issues unrelated to stroke * Use an electronically controlled medical device, such as a pacemaker, implanted defibrillator, or drug pump * Have numbness, tingling, muscle weakness, or pain in any part of your body * Have any skin related allergies or irritation to adhesives * Have blood circulation, heart, metabolic, or cognitive disorders, including but not limited to: Peripheral vascular disease, Pitting edema, Heart disease, Diabetes (uncontrolled), and Seizures.
About the study
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.
What is being tested
- A zero impedance mode, controlling a wearable bilateral hip exoskeleton (other)
- A personalized optimal assistance mode, controlling a wearable bilateral hip exoskeleton (other)
- A free walking mode, without wearing a wearable bilateral hip exoskeleton (other)
Sponsor: North Carolina State University · Participants: 100 · Started: Jun 1, 2022
Contact the study team
- Qiang Zhang, Ph.D. · Phone: 412-628-4758
- Laura Rohrbaugh · Phone: 919-513-3840
Official record on ClinicalTrials.gov — NCT05447884
Locations in the U.S.
| North Carolina | North Carolina State University, Raleigh |
Conditions
From ClinicalTrials.gov, data retrieved Nov 15, 2026. Each study sets its own eligibility; the study team decides who can join.