MAE SEMINAR: Toward dexterous control of assistive robotic hands using bi-directional neural-machine interface

Speaker: Dr. Xiaogang Hu

Abstract:

An intuitive neural interface is critical for effective communications between humans and assistive robots. We will discuss bi-directional noninvasive neural-machine interfaces that decode user intended movement and provide sensory feedback of the machine state and environment. We perform continuous decoding of intended finger movement based on spinal motoneuron firing activities, extracted from high-density electromyographic signals. It allows intuitive and robust control of individual fingers of a prosthetic hand. We also deliver somatosensory (tactile and proprioceptive) feedback to the user using electrical nerve stimulation and vibrotactile stimulation, in order to facilitate closed-loop control and object recognition. The Bi-directional neural interfaces have the potential to enable intuitive interactions of assistive robotic devices.

Bio:

Xiaogang Hu is an associate professor in the Joint Department of Biomedical Engineering at the University of North Carolina at Chapel Hill and North Carolina State University. He was trained in motor control and biomechanics at Penn State University during his PhD study, and he completed his postdoc training in stroke rehabilitation at the Rehabilitation Institute of Chicago or Northwestern University. His research interests focus on the human-machine interface and neural stimulation, targeting the upper limb functions of individuals after stroke or limb loss.