This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Zhijun L et al. Physical human–robot interaction of a robotic exoskeleton by admittance control. IEEE Transactions on Industrial Electronics. 2018,65(12):9614-9624.Search in Google Scholar
Parasuraman R, Sheridan TB, Wickens CD. A model for types and levels of human interaction with automation. IEEE Transactions on systems man and cybernetics-Part A: Systems and Humans. 2000; 30(3);286-297.Search in Google Scholar
Daley WD et al. Machine vision algorithm generation using human visual models. In: Precision Agriculture and Biological Quality. SPIE, 1999; 65-72.Search in Google Scholar
Cecil T, Grover CG, Royer FL. Models of contrast sensitivity in human vision. IEEE transactions on systems, man, and cybernetics. 1993,23(3):857-864.Search in Google Scholar
Toshikazu M. Theoretical reproduction of spatial frequency characteristics for reaction time based on a spatiotemporal human vision model with accommodative dynamics. Electronics and Communications in Japan (Part III: Fundamental Electronic Science). 1999;82(7):39-50.Search in Google Scholar
Sougata K et al. Application of digital human modeling and simulation for vision analysis of pilots in a jet aircraft: a case study. Work. 2012; 41(1):3412-3418.Search in Google Scholar
Mantiuk RK, Ramponi G. Human vision model including age dependencies. In: 2015 23rd European Signal Processing Conference (EUSIPCO). IEEE. 2015;1616-1620.Search in Google Scholar
Hirak M et al. Human visual system models in digital watermarking. In: 2015 International Conference and Workshop on Computing and Communication (IEMCON). IEEE. 2015; 1-7.Search in Google Scholar
Antoniewicz J. Automation principles. Wydawnictwa Naukowo-Techniczne. Warszawa 1965.Search in Google Scholar
Houshyar A et al. A review on otolith models in human perception. Behavioural brain research, 2016;309:67-76.Search in Google Scholar
Profilo Orcid