Ultrasound Imaging Based Sensing of Human Ankle Motion Intent and Control Strategies for Ankle Assistance
1 other identifier
interventional
25
1 country
2
Brief Summary
Robotic therapies aim to improve limb function in individuals with neurological injury. Modulation of robotic assistance in many of these therapies is achieved by measuring the extant volitional strength of limb muscles. However, current sensing techniques, such as electromyography, are often unable to correctly measure the voluntary strength of a targeted muscle. The difficulty is due to their inability to remove ambiguity caused by interference from activities of neighboring muscles. These discrepancies in the measurement can cause the robot to provide inadequate assistance or over-assistance. Improper robotic assistance slows function recovery, and can potentially lead to falls during robot-assisted walking. An ultrasound imaging approach is an alternative voluntary strength detection methodology, which can allow direct visualization and measurement of muscle contraction activities. The aim is to formulate an electromyography-ultrasound imaging-based technique to sense residual voluntary strength in ankle muscles for individuals with neuromuscular disorders. The estimated voluntary strength will be involved in the advanced controller's design of robotic rehabilitative devices, including powered ankle exoskeleton and functional electrical stimulation system. It is hypothesized that the ankle joint voluntary strength will be estimated more accurately by using the proposed electromyography-ultrasound imaging-based technique. And this will help the robotic rehabilitative devices achieve a more adaptive and efficient assistance control, and maximize the ankle joint rehabilitation training benefits.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for not_applicable
Started Feb 2020
Longer than P75 for not_applicable
2 active sites
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
Study Start
First participant enrolled
February 10, 2020
CompletedFirst Submitted
Initial submission to the registry
November 5, 2021
CompletedFirst Posted
Study publicly available on registry
February 21, 2022
CompletedPrimary Completion
Last participant's last visit for primary outcome
December 31, 2023
CompletedStudy Completion
Last participant's last visit for all outcomes
December 31, 2023
CompletedFebruary 21, 2022
February 1, 2022
3.9 years
November 5, 2021
February 16, 2022
Conditions
Keywords
Outcome Measures
Primary Outcomes (2)
Human volitional effort
The investigators calculate benchmark human volitional effort (torque \[N-m\]) using inverse dynamics. The investigators predict human volitional effort (torque \[N-m\]) using neuromuscular model and aforementioned outcome measures - sEMG, ultrasound imaging.
Through study completion, an average of 40 months.
Evaluate the controller performance of human ankle joint
The investigators measure the human ankle position \[rad\] and velocity \[rad/sec\] and the desired position \[rad\] and velocity \[rad/sec\] using a commercial sensor encoder when the controller is applied.
Through study completion, an average of 40 months.
Secondary Outcomes (4)
Human body joint kinematics
Through study completion, an average of 40 months.
Ground Reaction Forces
Through study completion, an average of 40 months.
Muscle activation level
Through study completion, an average of 40 months.
Muscle ultrasound image derived measures
Through study completion, an average of 40 months.
Study Arms (2)
Group A - Particiapnts without neurological disorders
EXPERIMENTALIndividuals without neurological disorders will be recruited (Group A).
Group S - Participants with iSCI or transverse myelitis
EXPERIMENTALIndividuals with neurological disorders, like iSCI or transverse myelitis, will be recruited (Group S). These individuals usually have weakened ankle joint functionalities but can walk independently.
Interventions
The study involves the validation of computer algorithms to estimate human ankle joint motion intent and control of ankle joint assistance by using either a powered exoskeleton or an FES system. The ankle joint motions will include seated posture tasks and walking tasks. The instrumented treadmill and Vicon motion capture system will be used to facilitate the cyclic walking pattern and record the participant's kinematics. The human ankle joint volitional effort will be predicted by the sEMG signals from shank muscles. The powered exoskeleton or FES system will provide ankle joint assistance based on an assist-as-needed strategy.
The study involves the validation of computer algorithms to estimate human ankle joint motion intent and control of ankle joint assistance by using either a powered exoskeleton or an FES system. The ankle joint motions will include seated posture tasks and walking tasks. The instrumented treadmill and Vicon motion capture system will be used to facilitate the cyclic walking pattern and record the participant's kinematics. The human ankle joint volitional effort will be predicted by the ultrasound imaging signals from shank muscles. The powered exoskeleton or FES system will provide ankle joint assistance based on an assist-as-needed strategy.
The study involves the validation of computer algorithms to estimate human ankle joint motion intent and control of ankle joint assistance by using either a powered exoskeleton or an FES system. The ankle joint motions will include seated posture tasks and walking tasks. The instrumented treadmill and Vicon motion capture system will be used to facilitate the cyclic walking pattern and record the participant's kinematics. The human ankle joint volitional effort will be predicted by combining sEMG and ultrasound imaging signals from shank muscles. The powered exoskeleton or FES system will provide ankle joint assistance based on an assist-as-needed strategy.
Eligibility Criteria
You may qualify if:
- Age between the ages of 18 and 64,
- Weight less than 220 lb,
- Able to perform ankle movements such as ankle up motion, ankle down motion, side motion towards inside, and side motion towards outside while seated, and
- Able to walk normally at a preferred speed without any assistive device.
You may not qualify if:
- Any difficulty or an orthopedic condition that would impede ankle movements such as ankle up motion, ankle down motion, side motion towards inside, and side motion towards outside,
- Any difficulty walking normally or without assistance,
- Absence of sensation in lower extremities,
- An allergy to adhesive skin tapes and/or US gels,
- Pregnant Females,
- No ankle muscle response to FES.
- years of age and have a primary diagnosis of traumatic/non-traumatic iSCI or demyelinating diseases like transverse myelitis,
- Weight less than 220 lb,
- Sub-acute or chronic phase (at least 3 months after injury) incomplete motor lesion (AIS C or D at enrollment) at cervical, thoracic or lumbar level,
- Ability to ambulate over ground independent using either a cane or rolling walker, as well as those that do not require any assistive devices but do have some mobility difficulties,
- Medically stable with medical clearance for participation, no evidence of cardiopulmonary or pulmonary disease, severe spasticity, and asymmetric hip positions,
- Ability to respond to FES on dorsiflexors and plantarflexors, and
- No use of any FES devices or already in use of a FES device for mobility support (like a Bioness device) but will not use the device during the study.
- Subjects with other neuromuscular diseases such as polio, stroke, or multiple sclerosis,
- Presence of transmissible diseases such as (but not limited to) hepatitis or immunodeficiency virus,
- +11 more criteria
Contact the study team to confirm eligibility.
Sponsors & Collaborators
- North Carolina State Universitylead
- University of North Carolina, Chapel Hillcollaborator
- U.S. National Science Foundationcollaborator
Study Sites (2)
1807 N. Fordham Blvd. UNC Center for Rehabilitation Care of Chapel Hill
Chapel Hill, North Carolina, 27514, United States
4212C Engineering Building III 1840 Entrepreneur Dr.
Raleigh, North Carolina, 27695, United States
Related Publications (4)
Zhang Q, Kim K, Sharma N. Prediction of Ankle Dorsiflexion Moment by Combined Ultrasound Sonography and Electromyography. IEEE Trans Neural Syst Rehabil Eng. 2020 Jan;28(1):318-327. doi: 10.1109/TNSRE.2019.2953588. Epub 2019 Nov 14.
PMID: 31725385BACKGROUNDZhang Q, Iyer A, Kim K, Sharma N. Evaluation of Non-Invasive Ankle Joint Effort Prediction Methods for Use in Neurorehabilitation Using Electromyography and Ultrasound Imaging. IEEE Trans Biomed Eng. 2021 Mar;68(3):1044-1055. doi: 10.1109/TBME.2020.3014861. Epub 2021 Feb 18.
PMID: 32759078BACKGROUNDZhang Q, Iyer A, Sun Z, Kim K, Sharma N. A Dual-Modal Approach Using Electromyography and Sonomyography Improves Prediction of Dynamic Ankle Movement: A Case Study. IEEE Trans Neural Syst Rehabil Eng. 2021;29:1944-1954. doi: 10.1109/TNSRE.2021.3106900. Epub 2021 Sep 27.
PMID: 34428143BACKGROUNDZhang Q, Sheng Z, Moore-Clingenpeel F, Kim K, Sharma N. Ankle Dorsiflexion Strength Monitoring by Combining Sonomyography and Electromyography. IEEE Int Conf Rehabil Robot. 2019 Jun;2019:240-245. doi: 10.1109/ICORR.2019.8779530.
PMID: 31374636BACKGROUND
MeSH Terms
Conditions
Condition Hierarchy (Ancestors)
Central Study Contacts
Study Design
- Study Type
- interventional
- Phase
- not applicable
- Allocation
- NON RANDOMIZED
- Masking
- NONE
- Purpose
- OTHER
- Intervention Model
- PARALLEL
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Associate Professor
Study Record Dates
First Submitted
November 5, 2021
First Posted
February 21, 2022
Study Start
February 10, 2020
Primary Completion
December 31, 2023
Study Completion
December 31, 2023
Last Updated
February 21, 2022
Record last verified: 2022-02
Data Sharing
- IPD Sharing
- Will not share
IPD will not be shared outside of this research group. However, selected data may be published in academic journals, conference papers, or other publications. This data will be de-identified, and will not include the full set of data.