Non-linear Granger causality and its frequency decomposition in decoding human upper limb movement intentions

Author(s):  
Meng Ting Liu ◽  
Ching Chang Kuo ◽  
Alan W.L. Chiu
Author(s):  
Zhi-Qiang Zhang ◽  
Lian-Ying Ji ◽  
Zhi-Pei Huang ◽  
Jian-Kang Wu

2019 ◽  
Vol 1345 ◽  
pp. 062024
Author(s):  
Ding Hao ◽  
Liu Shengchao ◽  
Jin Lulu ◽  
Gaofeng ◽  
Rui Qiaogen

Author(s):  
N Jarrassé ◽  
M Tagliabue ◽  
J V G Robertson ◽  
A Maiza ◽  
V Crocher ◽  
...  

HOMO ◽  
2005 ◽  
Vol 56 (1) ◽  
pp. 35-49 ◽  
Author(s):  
B. Gutnik ◽  
H. Mackie ◽  
G. Hudson ◽  
C. Standen

2021 ◽  
Vol 11 (13) ◽  
pp. 5865
Author(s):  
Muhammad Ahsan Gull ◽  
Mikkel Thoegersen ◽  
Stefan Hein Bengtson ◽  
Mostafa Mohammadi ◽  
Lotte N. S. Andreasen Struijk ◽  
...  

Wheelchair mounted upper limb exoskeletons offer an alternative way to support disabled individuals in their activities of daily living (ADL). Key challenges in exoskeleton technology include innovative mechanical design and implementation of a control method that can assure a safe and comfortable interaction between the human upper limb and exoskeleton. In this article, we present a mechanical design of a four degrees of freedom (DOF) wheelchair mounted upper limb exoskeleton. The design takes advantage of non-backdrivable mechanism that can hold the output position without energy consumption and provide assistance to the completely paralyzed users. Moreover, a PD-based trajectory tracking control is implemented to enhance the performance of human exoskeleton system for two different tasks. Preliminary results are provided to show the effectiveness and reliability of using the proposed design for physically disabled people.


Econometrics ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 17
Author(s):  
Konstantinos Gkillas ◽  
Christoforos Konstantatos ◽  
Costas Siriopoulos

We study the non-linear causal relation between uncertainty-due-to-infectious-diseases and stock–bond correlation. To this end, we use high-frequency 1-min data to compute daily realized measures of correlation and jumps, and then, we employ a nonlinear Granger causality test with the use of artificial neural networks so as to investigate the predictability of this type of uncertainty on realized stock–bond correlation and jumps. Our findings reveal that uncertainty-due-to-infectious-diseases has significant predictive value on the changes of the stock–bond relation.


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