Zhishan Guo
North Carolina State University, NC·Engineering
People who have lost part of a leg must work harder to walk than other people. They often walk unevenly, strain their lower back, and face a higher risk of falls.
- Fields
Engineering
Computer Science
Biomedical Engineering
- Topics
lower limb prosthesis
prosthetic robot
amputation
- Grants
- 1 known grant, through Jun 2027
What they work on
- Develop a gait capture method using only wearable inertial motion unit (IMU) sensors, using knowledge distillation so a multi-sensor teacher network trains a simpler IMU-only student network to predict walking in daily life.
- Design a lightweight, energy-efficient, semi-active prosthesis that combines air- and fluid-pressure (pneumatic-hydraulic) components so users can tune its settings for different environments.
- Create a reinforcement learning–based adaptive controller that coordinates the user and the prosthetic robot, using a mixed-criticality design from real-time systems to ensure safety and stability.
More about the research
Their eyes still see the terrain ahead, but that visual information can no longer guide the missing limb. Current robotic prostheses either respond too slowly and imprecisely or only work in controlled lab settings. This project aims to build a prosthetic robot that uses visual information to anticipate walking conditions. The robot would then adjust its control to each user in daily life.
Why it matters
People with lower limb amputation could benefit from a prosthesis that anticipates terrain and adapts to each user. Such a device could reduce the energy cost of walking, make gait more even, lower back strain, and reduce fall risk. Clinicians could also use the wearable gait-tracking tools to assess and prescribe prostheses outside the lab.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Zhaozheng Yin
Stony Brook University, NY·Computer Science
Develop motion capture from wearable inertial measurement unit (IMU) sensors alone to reconstruct and predict daily-life gait, using knowledge distillation from a multi-sensor teacher network to a simpler student network.
Tonya Stone
Mississippi State University, MS·Engineering
Design an elastic spring for an ankle foot prosthesis using machine learning-based optimization to determine the curvatures and contours that maximize energy return during walking.
Aaron Young
Georgia Institute of Technology, GA·Biomedical Engineering·Early-career
Compare personalized hip versus ankle exoskeleton assistance for improving walking on both legs after stroke, testing the hypothesis that hip assistance yields larger walking-speed gains because stroke survivors compensate at the hip for ankle weakness.
The school
North Carolina State University: 40 labs on PI Pages, $717M a year on research, 603 research doctorates a year.
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