An Analysis of Eye-Tracking and Electroencephalography Data for Cognitive Load Measurement during Arithmetic Tasks

被引：0
|
作者：
Borys, Magdalena [1 ]
Tokovarov, Mikhail [1 ]
Wawrzyk, Martyna [1 ]
Wesolowska, Kinga [1 ]
Plechawska-Wojcik, Malgorzata [1 ]
Dmytruk, Roman [1 ]
Kaczorowska, Monika [1 ]
机构：
[1] Lublin Univ Technol, Lublin, Poland
来源：
2017 10TH INTERNATIONAL SYMPOSIUM ON ADVANCED TOPICS IN ELECTRICAL ENGINEERING (ATEE) | 2017年
关键词：
biomedical data analysis; biomedical signal processing; eye-tracking analysis; EEG analysis; cognitive load; WORKING-MEMORY LOAD;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The paper presents multiple features analysis of cognitive load case study. The set of features applied in the research covers response times, committed errors, EEG spectral data as well as pupillometry and eye-tracking (ET) data including fixations, saccades and blinks. The experiment took the form of eleven intervals: six containing arithmetic tasks and five breaks. Two correlation analyses were performed. The first one aimed in finding correlation between cognitive measure, EEG and ET features in each interval. The second analysis was performed to find correlation of cognitive workload and EEG and ET features. The results proved that the best cognitive workload measures are selected eye movement and pupil dilation measures.
引用
收藏
页码：287 / 292
页数：6
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