12th Annual Delsys Prize Winner
Three-dimensional Innervation Zone Imaging from Noninvasive High-Density Surface EMG Recordings
Dr. Yingchun Zhang
University of Houston
United States of America
The study develops a novel 3D innervation zone (IZ) imaging approach (3DIZI) by combining the bioelectric activity imaging and surface EMG decomposition approaches to image the 3D IZ distribution or propagating internal muscle activities in target muscles from high-density surface EMG (HD-sEMG) recordings. This research is innovative because it represents the first effort to noninvasively localize IZs and propagating muscle activities in the 3D muscle space from HD-sEMG recordings, which is of great significance for a variety of application in research and clinical diagnosis for neuromuscular diseases such as ALS and muscle spasticity. This research will also lead to an advanced IZ-guided Botulinum neurotoxin (BTX) injection approach in treating muscle spasticity, which is not currently available in clinic.
About Dr. Yingchun Zhang
Yingchun Zhang, Ph.D is currently an Assistant Professor in the Department of Biomedical Engineering at the University of Houston. He received his PhD in Electrical Engineering at Zhejiang University, China, in collaboration with the Department of Biomedical Engineering at the University of Minnesota for biomedical signal processing, mathematical modeling and bioelectrical activity imaging methodologies. He completed his postdoctoral training in biomedical engineering, became a faculty member at the University of Minnesota Medical School in Jan, 2011, and took the position as an Assistant Professor in the Department of Biomedical Engineering at the University of Houston in Sep, 2012. Dr. Zhang is a recipient of NIH Pathway to Independence (K99/R00) award and serves as a reviewer for a number of peer-review scientific journals. His research interests focus on understanding the mechanisms of electromagnetic activities in biological tissue and systems, computational modeling and analysis of organ systems, and developing noninvasively functional imaging technologies to aid clinical diagnosis of dysfunction in the human body. He is also interested in utilizing developed functional imaging technologies to enhance human-machine-interface systems such as brain-computer-interface systems, brain-controlled devices, and myoelectrically-controlled prostheses.