TY - JOUR
T1 - Brain-computer interfaces for stroke rehabilitation
T2 - summary of the 2016 BCI Meeting in Asilomar
AU - Guger, Christoph
AU - Millán, José del R.
AU - Mattia, Donatella
AU - Ushiba, Junichi
AU - Soekadar, Surjo R.
AU - Prabhakaran, Vivek
AU - Mrachacz-Kersting, Natalie
AU - Kamada, Kyousuke
AU - Allison, Brendan Z.
N1 - Funding Information:
The work at g.tec was supported by the H2020 grant recoveriX. The work at EPFL was partially funded by the EU-ICT FP7-224631 project TOBI, the Swiss canton of Valais, and the Wyss Center for Bio and Neuroengineering in Geneva. The work at AAU was supported by the Obelske Familiefond of Denmark. FSL work was partially supported by the Italian Ministry of Healthcare.
Funding Information:
Keio University has received funding through three brain-machine interface (BMI)-related national projects from the Japan Agency for Medical Research and Development (AMED). AMED is a recently established national funding agency inspired by the National Institutes of Health (NIH) in the United States, aiming to promote integrated medical R&D from basic research to practical applications, to smoothly achieve application of outcomes, and to achieve comprehensive and effective establishment/maintenance of an environment for medical R&D. Keio University also received funding from the Strategic Research Program for Brain Sciences (SRPBS), which aims to explore the fundamental mechanisms and efficacies of BMI-based treatment of neurological disorders, as evidenced by neuroscientific measures. The next fund is from Future Medicine, which aims to bring neuroscientific BMI discoveries into the clinical setting by developing commercially available medical products through collaboration with world-wide industry makers/suppliers, such as Panasonic Corp. and Nihon Kohden Corp. The last supplementary fund from Future Medicine has supported the cost for investigator-initiated clinical trials. Through this strategic activity that spans fundamental, translational, and regulatory sciences, our research group, in collaboration with the Department of Rehabilitation Medicine, Keio University School of Medicine (PI: Meigen Liu), has been intensively developing BMI-based neurorehabilitation for stroke patients with severe hemiplegia.
Publisher Copyright:
© 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2018/7/3
Y1 - 2018/7/3
N2 - Brain-computer interfaces (BCIs) based on motor imagery have been gaining attention as tools to facilitate recovery from movement disorders resulting from stroke or other causes. These BCIs can detect imagined movements that are typically required within conventional rehabilitation therapy. This information about the timing, intensity, and location of imagined movements can help assess compliance and control feedback mechanisms such as functional electrical stimulation (FES) and virtual avatars. Here, we review work from eight groups that each presented recent results with BCI-based rehabilitation at a workshop during the 6th International Brain-Computer Interface Meeting. We also present major directions and challenges for future research.
AB - Brain-computer interfaces (BCIs) based on motor imagery have been gaining attention as tools to facilitate recovery from movement disorders resulting from stroke or other causes. These BCIs can detect imagined movements that are typically required within conventional rehabilitation therapy. This information about the timing, intensity, and location of imagined movements can help assess compliance and control feedback mechanisms such as functional electrical stimulation (FES) and virtual avatars. Here, we review work from eight groups that each presented recent results with BCI-based rehabilitation at a workshop during the 6th International Brain-Computer Interface Meeting. We also present major directions and challenges for future research.
KW - event-related desynchronization
KW - functional electrical stimulation
KW - motor imagery
KW - stroke rehabilitation
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U2 - 10.1080/2326263X.2018.1493073
DO - 10.1080/2326263X.2018.1493073
M3 - Article
AN - SCOPUS:85056754242
SN - 2326-263X
VL - 5
SP - 41
EP - 57
JO - Brain-Computer Interfaces
JF - Brain-Computer Interfaces
IS - 2-3
ER -