Operator functional state estimation based on EEG-data-driven fuzzy model

Jianhua Zhang; Zhong Yin; Shaozeng Yang; Rubin Wang

doi:10.1007/s11571-016-9389-x

Operator functional state estimation based on EEG-data-driven fuzzy model

Cogn Neurodyn. 2016 Oct;10(5):375-83. doi: 10.1007/s11571-016-9389-x. Epub 2016 May 13.

Authors

Jianhua Zhang¹, Zhong Yin², Shaozeng Yang¹, Rubin Wang³

Affiliations

¹ Department of Automation, East China University of Science and Technology, Shanghai, 200237 People's Republic of China.
² Engineering Research Center of Optical Instrument and System, Ministry of Education, University of Shanghai for Science and Technology, Shanghai, 200093 People's Republic of China.
³ Institute of Cognitive Neurodynamics, East China University of Science and Technology, Shanghai, 200237 People's Republic of China.

Abstract

This paper proposed a max-min-entropy-based fuzzy partition method for fuzzy model based estimation of human operator functional state (OFS). The optimal number of fuzzy partitions for each I/O variable of fuzzy model is determined by using the entropy criterion. The fuzzy models were constructed by using Wang-Mendel method. The OFS estimation results showed the practical usefulness of the proposed fuzzy modeling approach.

Keywords: Entropy; Fuzzy modeling; Fuzzy partition; Operator functional state; Wang–Mendel method.