Real-time BMI using ECoG for paralyzed patients

Abstract

Event Abstract Back to Event Real-time BMI using ECoG for paralyzed patients Ryohei Fukuma1, 2* 1 Osaka University Graduate School of Medicine, Department of Neurosurgery, Japan 2 ATR Computational Neuroscience Laboratories, Department of Neuroinformatics, Japan A neuroprosthesis using a brain-machine interface (BMI) is a promising therapeutic option for severely paralyzed patients. However, typical high-performance BMIs require microelectrodes, which damage cortex and lack long-term stability of signals. We have developed a neuroprosthesis controlled by real-time electrocorticogram (ECoG), and adapted the neuroprosthesis to paralyzed patients. In this talk, I first demonstrate characteristic features in the ECoG signals of paralyzed patients, and the representation about the movement of paralyzed limb. The spatial pattern of high-γ power coded information about movements, and by using machine-learning approach, the information could be successfully extracted to control the neuroprosthesis. Next, I introduce an experiment, in which ECoG-based BMI was adapted to an amyotrophic lateral sclerosis (ALS) patient. In this experiment, the patient succeeded in controlling the neuroprosthesis and typing words on computer, using motor imagery. This is the first report to show the successful communication using ECoG from the ALS patient. Finally, I discuss new approaches to realize practical ECoG-based BMI. Keywords: ECoG, Brain machine interface (BMI), Amyotrophic lateral sclerosis (ALS), Paralysis, machine learning Conference: German-Japanese Adaptive BCI Workshop, Kyoto, Japan, 28 Oct - 29 Oct, 2015. Presentation Type: Oral presentation (Invited speakers) Topic: Adaptive BCI Citation: Fukuma R (2015). Real-time BMI using ECoG for paralyzed patients. Front. Comput. Neurosci. Conference Abstract: German-Japanese Adaptive BCI Workshop. doi: 10.3389/conf.fncom.2015.56.00005 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 15 Oct 2015; Published Online: 04 Nov 2015. * Correspondence: Dr. Ryohei Fukuma, Osaka University Graduate School of Medicine, Department of Neurosurgery, Suita, Osaka, Japan, r-fukuma@nsurg.med.osaka-u.ac.jp Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Ryohei Fukuma Google Ryohei Fukuma Google Scholar Ryohei Fukuma PubMed Ryohei Fukuma Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.