Shared control architecture based on RFID to control a robot arm using a spontaneous brain–machine interface

2013 ◽  
Vol 61 (8) ◽  
pp. 768-774 ◽  
Author(s):  
Andrés Úbeda ◽  
Eduardo Iáñez ◽  
José M. Azorín
Keyword(s):  
Shared Control ◽  
Control Architecture ◽  
Brain Machine Interface ◽  
Robot Arm ◽  
Machine Interface

Development of Brain Machine Interface for Operation of Auxiliary Robot Arm

2019 ◽  
Vol 2019 (0) ◽  
pp. 2A2-L05
Author(s):  
Yoshiyuki Tsuda ◽  
Shoshiro Hatakeyama ◽  
Masami Iwase ◽  
Jun Inoue
Keyword(s):  
Brain Machine Interface ◽  
Robot Arm ◽  
Machine Interface

scholarly journals Control of a Robot Arm Using Decoded Joint Angles from Electrocorticograms in Primate

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Duk Shin ◽  
Hiroyuki Kambara ◽  
Natsue Yoshimura ◽  
Yasuharu Koike
Keyword(s):  
Linear Regression ◽  
Degree Of Freedom ◽  
Coefficient Of Determination ◽  
Brain Machine Interface ◽  
Robot Arm ◽  
Joint Angles ◽  
Machine Interface ◽  
Electrocorticogram Ecog ◽  
Muscle Activations ◽  
Best Fit

Electrocorticogram (ECoG) is a well-known recording method for the less invasive brain machine interface (BMI). Our previous studies have succeeded in predicting muscle activities and arm trajectories from ECoG signals. Despite such successful studies, there still remain solving works for the purpose of realizing an ECoG-based prosthesis. We suggest a neuromuscular interface to control robot using decoded muscle activities and joint angles. We used sparse linear regression to find the best fit between band-passed ECoGs and electromyograms (EMG) or joint angles. The best coefficient of determination for 100 s continuous prediction was 0.6333 ± 0.0033 (muscle activations) and 0.6359 ± 0.0929 (joint angles), respectively. We also controlled a 4 degree of freedom (DOF) robot arm using only decoded 4 DOF angles from the ECoGs in this study. Consequently, this study shows the possibility of contributing to future advancements in neuroprosthesis and neurorehabilitation technology.

A Bayesian Shared Control Approach for Wheelchair Robot With Brain Machine Interface

2020 ◽  
Vol 28 (1) ◽  
pp. 328-338 ◽  
Author(s):  
Xiaoyan Deng ◽  
Zhu Liang Yu ◽  
Canguang Lin ◽  
Zhenghui Gu ◽  
Yuanqing Li
Keyword(s):  
Shared Control ◽  
Brain Machine Interface ◽  
Control Approach ◽  
Machine Interface

A shared control policy for center-out movement decoding in motor Brain-machine Interface

2013 ◽  
Vol 46 (20) ◽  
pp. 345-348 ◽  
Author(s):  
Xi Chen ◽  
Yuxi Liao ◽  
Yiwen Wang ◽  
Shaomin Zhang ◽  
Qiaosheng Zhang ◽  
...  
Keyword(s):  
Control Policy ◽  
Shared Control ◽  
Brain Machine Interface ◽  
Machine Interface
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