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Closed-loop peripheral sensory augmentation and its effect on motor control


Title: Closed-loop peripheral sensory augmentation and its effect on motor control


2021.6.7(mon) 4PM


Texas A&M Univ., Prof. Hangue Park



Nervous system is highly adaptive to cope with the changes. But the natural neural adaptation is often not optimal and results in undesirable secondary conditions. If we interface and communicate with the nervous system, we might able to guide the neural adaptation to the proper direction. Electrical circuits and systems can favorably intervene the nervous system operation, as the neural signal can be recorded by electrical circuits and modulated by electrical stimulation (E-stim) at the right timing as a closed loop. The closed-loop E-stim has been applied in multiple ways to modulate ascending sensory feedback or descending motor commands. In this talk, I will introduce one approach of this closed-loop E-stim, applied onto peripheral sensory nerves. The closed-loop E-stim not only augments sensory feedback but also modulates motor output in a desired way. I will also share multiple human and animal experimental data to show the efficacy of the closed-loop E-stim on peripheral sensory nerves.



Hangue Park is currently an assistant professor in Electrical and Computer Engineering at Texas A&M University. He received his Ph.D. in Electrical and Computer Engineering at Georgia Institute of Technology, in 2017. At Georgia Tech, he worked for multiple human and animal studies with people after spinal cord injury and amputee cats. He also has 5+ years of industrial experience in circuit and system design for cell phone and handheld electronic devices. His current research interests lie in artificial sensory feedback and closed-loop optimization of sensorimotor loop, to assist incomplete body functions and enhance rehabilitation outcomes. He is a recipient of the Trainee Professional Development Award from Society for Neuroscience at 2017, the Outstanding Research Award from the Association of Korean Neuroscientists at 2016, and the Best Demonstration Award at the IEEE Biomedical Circuits and Systems Conference 2012.





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