Method for operator mental workload assessment based on power spectral density of EEG

ZHANG Jie; PANG Liping; WANYAN Xiaoru; CHEN Hao; WANG Xin; LIANG Jin

doi:10.7527/S1000-6893.2019.23618

ACTA AERONAUTICAET ASTRONAUTICA SINICA >

2020 , Vol. 41 >Issue 10: 123618 - 123618

DOI: https://doi.org/10.7527/S1000-6893.2019.23618

Fluid Mechanics and Flight Mechanics

Method for operator mental workload assessment based on power spectral density of EEG

ZHANG Jie ,
PANG Liping ,
WANYAN Xiaoru ,
CHEN Hao ,
WANG Xin ,
LIANG Jin

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1. School of Aeronautic Science and Engineering, Beihang University, Beijing 100083, China;
2. Marine Human Factors Engineering Lab, China Institute of Marine Technology & Economy, Beijing 100081, China

Received date: 2019-10-31

Revised date: 2020-01-03

Online published: 2020-01-02

Supported by

The Jointly Program of National Natural Science Foundation of China and Civil Aviation Administration of China (U1733118);The Liao Ning Revitalization Talents Program (XLYC1802092)

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Abstract

The accurate recognition of mental workload levels is of great significance to reduce human accidents caused by operators with invalid mental workload. This paper focuses on the objective mental workload assessment of operators in human-machine system. An aviation situational experiment based on MATB-Ⅱ was carried out at three levels of mental workload. Sixteen subjects were asked to fill in the NASA-Task Load Index (NASA-TLX) scale and the Electroencephalogram (EEG) results during the experiment were recorded. By analyzing the collected subjective and physiological data, a subject-specified mental workload assessment method was proposed using the Power Spectral Density (PSD) of EEG and the Support Vector Machine (SVM). The results show that the subjective mental workload scores increase significantly (p<0.001) with the increase of designed mental workload levels, indicating that the experimental design successfully induces different mental workload scenarios. Based on the rationality of the experimental design, the subject-specified mental workload assessment models are established, and the parameters of these models are optimized by grid search and then unified as the penalty parameter of 3 000 and the kernel function parameter of 0.000 1. The test accuracy reaches 0.966 5±0.029 8, and the area under Macro-Averaging receiver operating Characteristic curve (Macro-AUC) reaches 0.991 0±0.011 4. Thus, the models provide a new approach for the objective and accurate assessment of mental workload, providing a basis for the real-time discrimination of mental workload.

Key words： mental workload; NASA-task load index; power spectral density; support vector machine; subject-specified discrimination model

Cite this article

ZHANG Jie , PANG Liping , WANYAN Xiaoru , CHEN Hao , WANG Xin , LIANG Jin . Method for operator mental workload assessment based on power spectral density of EEG[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2020 , 41(10) : 123618 -123618 . DOI: 10.7527/S1000-6893.2019.23618

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