Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces-Reference-Cited by-同舟云学术

Wireless Soft Scalp Electronics and Virtual Reality System for Motor Imagery‐Based Brain–Machine Interfaces

Published:2021-07-17 Issue:19 Volume:8 Page:2101129
ISSN:2198-3844
Container-title:Advanced Science
language:en
Short-container-title:Adv. Sci.

Author:

Mahmood Musa¹²,Kwon Shinjae¹²,Kim Hojoong¹²,Kim Yun‐Soung¹²,Siriaraya Panote³,Choi Jeongmoon⁴,Otkhmezuri Boris³,Kang Kyowon⁵,Yu Ki Jun⁵,Jang Young C.⁴,Ang Chee Siang³,Yeo Woon‐Hong¹²⁶^ORCID

Affiliation:

1. George W. Woodruff School of Mechanical Engineering College of Engineering Georgia Institute of Technology Atlanta GA 30332 USA

2. Center for Human‐Centric Interfaces and Engineering Institute for Electronics and Nanotechnology Georgia Institute of Technology Atlanta GA 30332 USA

3. School of Computing University of Kent Canterbury Kent CT2 7NT UK

4. School of Biological Sciences, College of Sciences Georgia Institute of Technology Atlanta GA 30332 USA

5. School of Electrical and Electronic Engineering Yonsei University Seoul 03722 Republic of Korea

6. Wallace H. Coulter Department of Biomedical Engineering Parker H. Petit Institute for Bioengineering and Biosciences Institute for Materials Neural Engineering Center Institute for Robotics and Intelligent Machines Georgia Institute of Technology Atlanta GA 30332 USA

Funder

National Institutes of Health

National Research Foundation of Korea

Publisher

Wiley

Subject

General Physics and Astronomy,General Engineering,Biochemistry, Genetics and Molecular Biology (miscellaneous),General Materials Science,General Chemical Engineering,Medicine (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/advs.202101129

Reference38 articles.

1. EEG-Based Brain-Computer Interfaces Using Motor-Imagery: Techniques and Challenges

2. Applications of Brain–Machine Interface Systems in Stroke Recovery and Rehabilitation

3. Fully portable and wireless universal brain–machine interfaces enabled by flexible scalp electronics and deep learning algorithm

4. Soft, curved electrode systems capable of integration on the auricle as a persistent brain–computer interface

5. Soft Material-Enabled, Flexible Hybrid Electronics for Medicine, Healthcare, and Human-Machine Interfaces

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