Bulea – Rubin – 2026

Developing Novel Sensing Methods for Pediatric Exoskeletons

The Neurorobotics Research Group developed a commercial-grade lower-limb exoskeleton that is now used as a rehabilitation therapy for pediatric gait training. Building on years of development, our team is conducting an interventional study in which children with cerebral palsy, muscular dystrophy, incomplete spinal cord injury, or spina bifida complete a prescribed exoskeleton gait training program designed to reduce crouch gait at using the exoskeleton at home.

In parallel, we have been developing new methods to deploy our exoskeleton in support of more complex community-relevant mobility tasks, such as ramp and stair negotiation and obstacle avoidance. Key next steps in advancing the system toward ubiquitous, real-world use are (1) improving the exoskeleton’s ability to infer user intent and device state in real-time and (2) exploring hybrid intervention strategies that can augment robotic assistance to enhance therapeutic outcomes and adaptability across diverse environments.

To help accomplish this goal, this summer project will focus on integrating new sensing and/or hybrid therapy components into the existing exoskeleton platform (e.g., inertial measurement units (IMUs) and/or functional electrical stimulation (FES)), with an emphasis on hardware integration and reliable data acquisition in realistic task conditions.

What the intern will do (with mentorship):

• Prototype and integrate new hardware into an existing wearable robotic system (mechanical design, mounting, cable routing/strain relief, safety considerations, iterative testing) with an emphasis on robustness, usability, and simple, repeatable installation across a range of both adult and pediatric users
• Implement and validate sensor data acquisition into existing software pipelines, and assess data quality and consistency in controlled bench tests and protocol-relevant tasks (walking on ramps, stairs, and obstacle course elements)
• In parallel, create clear, well-structured system and test documentation to facilitate long-term adoption by the team
• Stretch goals:
  • Highly motivated and successful interns may have the opportunity to implement and test their system in children with movement disorders in our clinical gait lab
  • Data processing, analysis, and feature extraction to infer device/user state (e.g., gait event detection, task classification, signal quality monitoring etc.)
  • Modify existing real-time robotic control algorithms to incorporate newly integrated components