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Rehabilitation Treatment of Motor Dysfunction Patients Based on Deep Learning Brain–Computer Interface Technology

Huihai Wang, Qinglun Su, Zhenzhuang Yan, Fei Lu, Qin Zhao, Zhen Liu, Fang Zhou
2020 Frontiers in Neuroscience  
Based on the research and implementation of a BCI system based on a convolutional neural network, this article aims to design a brain-computer interface system that can automatically extract features of  ...  In recent years, brain-computer interface (BCI) is expected to solve the physiological and psychological needs of patients with motor dysfunction with great individual differences.  ...  ACKNOWLEDGMENTS We thank the reviewers whose comments and suggestions helped improve this manuscript.  ... 
doi:10.3389/fnins.2020.595084 pmid:33192282 pmcid:PMC7642128 fatcat:dql3kksmt5gijhllpe2bmx5ptq

Current Status, Challenges, and Possible Solutions of EEG-Based Brain-Computer Interface: A Comprehensive Review

Mamunur Rashid, Norizam Sulaiman, Anwar P. P. Abdul Majeed, Rabiu Muazu Musa, Ahmad Fakhri Ab. Nasir, Bifta Sama Bari, Sabira Khatun
2020 Frontiers in Neurorobotics  
This article provides a comprehensive review of the state-of-the-art of a complete BCI system. First, a brief overview of electroencephalogram (EEG)-based BCI systems is given.  ...  Brain-Computer Interface (BCI), in essence, aims at controlling different assistive devices through the utilization of brain waves.  ...  ACKNOWLEDGMENTS The authors would like to acknowledge support from the Faculty of Electrical & Electronics Engineering Technology, Universiti Malaysia Pahang, Malaysia.  ... 
doi:10.3389/fnbot.2020.00025 pmid:32581758 pmcid:PMC7283463 fatcat:jhpwp2b3hffz5mazb7y6oj3saq

An ECoG-Based Binary Classification of BCI Using Optimized Extreme Learning Machine

Xinman Zhang, Qi Xiong, Yixuan Dai, Xuebin Xu, Guokun Song
2020 Complexity  
In order to improve the accuracy of brain signal processing and accelerate speed meanwhile, we present an optimal and intelligent method for large dataset classification application in this paper.  ...  Optimized Extreme Learning Machine (OELM) is introduced in ElectroCorticoGram (ECoG) feature classification of motor imaginary-based brain-computer interface (BCI) system, with common spatial pattern (  ...  In China, the BCI research team from Tsinghua University has designed an automatic dialing system that controls telephone, which is connected to a computer for real-time dial by interpreting brain thinking  ... 
doi:10.1155/2020/2913019 fatcat:odzbvap7wnbcliusplzxcqs6bi

Final Program, Abstracts Presented at the Thirty–Fifth Annual International Neuropsychological Society Conference, February 7–10, Portland, Oregon, USA

2007 Journal of the International Neuropsychological Society  
Despite this, there were no differences on any of the depression measures.  ...  Furthermore, depression proneness accounted for about three times the variance in SP patients compared to RR patients (r2=.61 versus .20).  ...  Each sensor generated signals of three dimensional coordinates of its center point and the orientation of a local coordinate system affixed to the sensor in a reference coordinate system on a common receiver  ... 
doi:10.1017/s1355617707079969 fatcat:hyqc3ut5ybg3rnk6shatuylham

ACRT-AFMR-SCTS Annual Meeting Abstracts

2011 Clinical and Translational Science  
a major impact on the subsequent health of individuals throughout their lives.  ...  REDCap soft ware is available at no fi nancial charge to academic and nonprofi t institutions through a consortium network (www.project-redcap. org).  ...  We propose electrocorticography (ECoG) as a realistic approach that strikes an optimal balance in the tradeoff s associated with neural signal quality, invasiveness, system complexity, and maintenance.  ... 
doi:10.1111/j.1752-8062.2011.00269.x fatcat:conrvqsnzrbk5hgs74ou352fey

Proceedings of the 13th Russian German Conference on Biomedical Engineering

Steffen Leonhardt, Steffen Leonhardt
2018
Acknowledgements J.Ch.S. is grateful for a stipend and financial support for this project from Prince of Songkla University, Thailand.  ...  Acknowledgement The author is grateful for the financial support of the work by Russian Science Foundation (grant 18-29-02108 mk).  ...  Convolutional neural network (CNN) is a type of feedforward artificial neural network and is usually applied to two-dimensional signals i.e. images.  ... 
doi:10.18154/rwth-2018-224393 fatcat:vu735cealrczzc7aiwmzojoczm

Fused mechanomyography and inertial measurement for human-robot interface

Samuel Charles Wilson, Ravi Vaidyanathan, Alison McGregor, US Office Of Naval Research Global, Engineering And Physical Sciences Research Council, UK-India Educational Research Initiative, Royal British Legion, UK Medtech Superconnector Fund, SERG Technologies
2020
The fundamental goal of an HMI is to facilitate robot control through uniting a human operator as the supervisor with a machine as the task executor.  ...  and generation of robotic control signals.  ...  Ravi Vaidyanathan and Professor Alison McGregor for giving me the opportunity to pursue this work and the advice and guidance to complete it.  ... 
doi:10.25560/80267 fatcat:q5hx4u62dvfndf3xubcfeecwb4