CAREER: Versatile Wearable Robots for Rehabilitation of Children with Gait Disabilities

  • Su, Hao (Investigador principal)

Detalles del proyecto

Descripción

This Faculty Early Career Development (CAREER) grant seeks to enhance the usability and comfort of a powered knee exoskeleton that is designed to improve gait biomechanics and walking metabolic economy in children with cerebral palsy. By leveraging novel actuators and wearable sensor technology, the PI will develop an exoskeleton system that can "grow" in capability as the child grows. The PI will also design a task-recognition system (intent estimation) that facilitates high-level exoskeleton control. That high-level control is augmented using a model-free adaptive controller that can provide user-specific joint torque assistance. This project will promote the progress of science and advance the national health by establishing theoretical foundations for - and a physical realization of - a new approach to rehabilitating pediatric gait, one that is safe, lightweight, compliant, smart, and able to be used in community settings. An integrated research and education plan and innovative outreach activities targeted to elementary- and high-school students will promote a globally competitive STEM workforce and the participation of women and underrepresented minorities in STEM. Efforts to further develop a "Soft Robot Zoo" will increase public scientific literacy and engagement with robotics.This project seeks to reduce gait impairments in children with cerebral palsy using a novel powered knee exoskeleton that can anticipate changing needs for joint torque assistance based on changing task conditions as well as changing user intentions with regard to gait transitions. Three main research objectives are researched: an optimization of human-machine interaction using "quasi-direct drive actuated" wearable robotics; kinematic activity classification and gait mode detection in children with cerebral palsy using wearable sensor technology; and the development of a reinforcement learning (RL-based) adaptive controller for assistive joint torque personalization. Taken together, these research activities promise to enhance human/machine collaboration in a real-world setting for children contending with physical disability.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.
EstadoActivo
Fecha de inicio/Fecha fin15/2/2231/3/25

Financiación

  • National Science Foundation: USD552,308.00

!!!ASJC Scopus Subject Areas

  • Inteligencia artificial
  • Ingeniería (todo)
  • Ingeniería civil y de estructuras

Huella digital

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