Each year, more than 17,000 people in the United States experience a spinal cord injury. Individuals suffering from incomplete spinal cord injuries may have voluntary control of their limbs, but their strength is weakened compared to able-bodied persons. Neurorehabilitation is a therapeutic approach used to recover limb function in individuals suffering from incomplete spinal cord injury; robotic or electrical stimulation devices encourage repair of the person's nervous system through repeated, assisted exercise. The amount of assistance the device provides is based upon the user's remaining muscle function. However, correctly measuring a person's voluntary effort during therapeutic exercise is a significant technical challenge. Discrepancies in the measurement can cause the robot to provide too much or too little assistance, which can slow recovery and lead to falls during robot-assisted walking. To address the technical challenge of sensing of voluntary effort, this project will integrate ultrasound imaging with electromyography-based (i.e., electrical signals) measurement of ankle muscles that govern walking. The use of ultrasound imaging will allow direct visualization and measurement of muscle activity and minimizes interference of electrical signals from neighboring muscles. Ultrasound imaging will also be investigated as an approach for optimizing electrode placement to initiate multi-plane ankle movements. The study will test the hypothesis that ultrasound imaging-based measurement of voluntary effort is more accurate than electromyography-based prediction alone. Research and education are integrated through student-led construction of ultrasound imaging and electromyography-based human-machine interaction platforms for children with special needs. The human-machine interaction platforms may accelerate learning in children with special needs and offers research opportunities for high school-age students from underrepresented groups in STEM.

The PI's long-term career goal is to build a full-scale, feedforward musculoskeletal model that predicts human intent by obtaining signals from wearable ultrasound sensors attached to different limb muscles. Toward this goal, the project will derive control strategies that use ultrasound imaging to predict weakened voluntary effort of a person with incomplete spinal cord injury and provide assistance as-needed during walking with a hybrid exoskeleton. The research objectives of the proposal are to: (1) formulate an ultrasound imaging-based observer to predict voluntary effort in ankle muscles and (2) use the prediction in an ankle control strategy. An optimal ultrasound imaging-derived surrogate signal to measure voluntary effort will be determined, and a functional mapping between the surrogate signals and voluntary effort will be formulated. The stability and convergence conditions for the observer and the ankle controller will be established. The new intent prediction and control framework will be directly compared to electromyography-based prediction and control methods. Functional electrical stimulation of the ankle muscles that produce multi-plane ankle movements will also be investigated. To target the intended ankle muscle, ultrasound imaging-based feedback will be evaluated to optimize current in the stimulation electrodes. The project facilitates a breakthrough rehabilitation therapy that uses non-invasive, wearable ultrasound sensors to collect, monitor, and control muscle activity of persons with incomplete spinal cord injury.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Start
Project End
Budget Start
2019-09-01
Budget End
2023-06-30
Support Year
Fiscal Year
2020
Total Cost
$381,454
Indirect Cost
Name
North Carolina State University Raleigh
Department
Type
DUNS #
City
Raleigh
State
NC
Country
United States
Zip Code
27695