Understanding nerve activity is something Dr. Zachary Danziger, assistant professor in the Biomedical Engineering Department at the College of Engineering & Computing, has been researching for years. Through the National Science Foundation (NSF) Danziger, as the principal investigator, has been awarded a $480,000.00 grant to research and further investigate how large sets of control variables can be organized to optimize how people learn to control complex machines. A notable component for getting this award came as a contribution by Steafan Khan, a member of Dr. Danzinger’s laboratory and a Biomedical Engineering Ph.D. student working in the area of motor learning and neuroscience. Mr. Khan was responsible for creating a prototype system as a proof of concept, which led to this funding.
This Non-Invasive Models of Human Brain-Computer-Interface Control of Robots project seeks to promote the progress of science and advance national health by addressing two questions related to the design and implementation of adaptive brain-machine interfaces such as those used by severely impaired people to control assistive robotics. An important novelty of the researched approach is the non-invasive recording of finger motions as a proxy for the high-dimensional inputs typically provided by intracortical brain-computer interfaces (iBCI).
There are many situations where a skilled human operator must manipulate a large number of control variables in real-time to direct the dexterous motion of a robotic device such as a surgical robot, or operating a cutting-edge brain-controlled prosthetic limb. This research is primarily focused on finding out how should control signals be presented to the user at the control interface to optimize the output behavior of the machine and, how should task-level control be shared between the user and the machine to optimize task performance? To arrive at possible conclusions, the project will use two models of intracortical brain-computer interfaces (iBCI) to evaluate how high-dimensional human input should be mapped onto command variables for a 6 degree-of-freedom embodied robotic arm. The project uses a non-invasive recording of finger motions as a proxy for the high-dimensional inputs typically provided by iBCIs.
Professor Danziger is the director of FIU’s Applied Neural Interfaces Lab, a lab focused on understanding and modeling the neuropathophysiology of disease with the goal of engineering new devices that interface with the nervous system to improve people’s lives. Students looking to study and research Therapeutic and Reparative Neurotechnology should contact Dr. Danziger or visit his lab (https://anil.fiu.edu) to learn more about his ongoing research. For in-depth research training and biomedical engineering coursework and degrees, please visit our degree programs page.
Zachary Danziger, Ph.D.
Research Advancements: Zachary Danziger is making strides in understanding bladder control in aging and spinal cord injury.
Research Area: Therapeutic and Reparative Neurotechnology
Lab: Applied Neural Interfaces Laboratory