Measuring Cognitive Workload in Arithmetic Tasks Based on Response Time and EEG Features

被引：3

作者：

Plechawska-Wojcik, Malgorzata ^{[1
]}

Borys, Magdalena ^{[1
]}

Tokovarov, Mikhail ^{[1
]}

Kaczorowska, Monika ^{[1
]}

机构：

[1] Lublin Univ Technol, Lublin, Poland

来源：

INFORMATION SYSTEMS ARCHITECTURE AND TECHNOLOGY, PT I | 2018年 / 655卷

关键词：

EEG; Spectral analysis; Cognitive workload; FFT; ERP; MENTAL WORKLOAD; LOAD;

D O I：

10.1007/978-3-319-67220-5_6

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The aim of the present paper is to verify whether the cognitive load can be evaluated through the analysis of the examined person's response time and extracted EEG signal features. The research was based on an experiment consisting of six intervals ensuring various cognitive load level of arithmetic tasks. The paper describes in details the analysis process including signal pre-processing with artifact correction, feature extraction and outlier detection. Statistical verification of EEG band differences, response time and error rate in intervals was realised. Statistical correlations were found between EEG features and response time, however, the correlation strength increased inside the groups of intervals of similar cognitive workload level. Evoked related potentials were also analysed and their results confirmed the statistical outcomes.

引用

页码：59 / 72

页数：14

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