Ultrasound Imaging Based Sensing of Human Ankle Motion Intent and Control Strategies for Ankle Assistance

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.

Conditions

• Incomplete Spinal Cord Injury
• Transverse Myelitis

Interventions

DEVICE

Surface electromypgraphy-based interface to predict human ankle joint motion intent and use in ankle assistive devices

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.

DEVICE

Ultrasound imaging-based interface to predict human ankle joint motion intent and use in ankle assistive devices

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.

DEVICE

Surface electromypgraphy and ultrasound imaging-based interface to predict human ankle joint motion intent and use in ankle assistive devices

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.

Sponsors & Collaborators

• University of North Carolina, Chapel Hill

  collaborator OTHER

• U.S. National Science Foundation

  collaborator FED

• North Carolina State University

  lead OTHER

Study Design

Allocation

NON_RANDOMIZED

Purpose

OTHER

Masking

NONE

Model

PARALLEL

Eligibility

Min Age

18 Years

Max Age

64 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2020-02-10

Primary Completion

2023-12-31

Completion

2023-12-31

Countries

• United States

Study Locations