This program supports the development and demonstration of broadly applicable robotic systems to enable new paradigms of human health.
The emphasis is on the development of robotic systems hardware, software, and methodologies to improve patient health.
NIBIB interests include but are not limited to:
- robots for minimally invasive surgeries
microgrippers and drills for surgical robots
robotic nurses for isolated patient care
soft robotic exoskeletons to replace lost capabilities
soft elastomeric actuators for assistive robotics
December 7, 2023
NIH-funded researchers have outlined a method to print biocompatible structures through thick, multi-layered tissues using focused ultrasound.
October 20, 2023
Navigating the labyrinthine vasculature of the brain with standard surgical instruments can be incredibly challenging, even for the steadiest of hands. But with some robotic assistance, brain surgeons could potentially operate with far greater ease.
October 16, 2023
Dendritic cells are key orchestrators of the immune response, but most vaccination strategies don’t effectively target them. NIBIB-funded researchers have developed biodegradable nanoparticles that are designed to deliver mRNA cargo to dendritic cells in the spleen. Combined with another type of immunotherapy, their vaccine had robust antitumor effects in multiple mouse models.
June 29, 2023
A first-of-its-kind robotic glove is lending a “hand” and providing hope to piano players who have suffered a disabling stroke. Developed by researchers from Florida Atlantic University’s College of Engineering and Computer Science, the soft robotic hand exoskeleton uses artificial intelligence to improve hand dexterity. Source: Boca Raton Tribune
June 20, 2023
A team of researchers has developed a new method for controlling lower limb exoskeletons using deep reinforcement learning. The method enables more robust and natural walking control for users of lower limb exoskeletons. The study, "Robust walking control of a lower limb rehabilitation exoskeleton coupled with a musculoskeletal model via deep reinforcement learning," is available open access. Source: Kessler Foundation/Science Daily