Computational approach to high performance Rehabilitation using Brain-machine Interface paradigm
Jaeseung Jeong
Abstract : For motor-disabled patients with Stroke or brain tumor, one of the most effective treatments is to induce reorganization of the motor cortex and related areas damaged by neurological disorders to restore its own function. However, this potentially requires a computational model of its network based on an understanding of the movement-related cerebral cortex and subcortical regions from the cellular to the systems level. In this talk, we introduce the major findings of brain-machine interface approach to stroke patients that we obtained so far. In addiiton, we demonstrate an attempt to apply this approach to stroke patients through both exoskeleton and brain-machine interface for their physical and occupational therapies. Based on these preliminary studies, we suggest a plan of computer modeling approach to efficient rehabilitation for Stroke patients and other neurological disorder patients to recover their motor function.
Bio : Professor Jaeseung Jeong is currently a professor at the Department of Bio and Brain Engineering, and the Head of Graduate School of Future Strategy in KAIST (Daejeon, South Korea). He received Ph.D. from Department of Physics in KAIST. He has been working as a postdoc associate at the Department of Psychiatry, School of Medicine in Yale University (New Haven, USA) and as an assistant professor at the Department of Psychiatry, College of Physicians and Surgeons in Columbia University (New York, USA). His research topics include brain dynamics of decision-making, computational modeling of neuropsychiatric disorders including depression, addiction, and dementia, Brain-Robot Interface (BRI), and Brain-inspired Artificial Intelligence. He was selected as one of ‘Young Global Leaders’ from World Economic Forum (WEF a.k.a. Davos Forum) in 2009 and received several awards from scientific communities.
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