Cognitive load and metacognitive confidence extraction from pupillary response

被引:15
|
作者
Gavas, Rahul D. [1 ]
Tripathy, Soumya Ranjan [2 ]
Chatterjee, Debatri [1 ]
Sinha, Aniruddha [1 ]
机构
[1] Tata Consultancy Serv, Embedded Syst & Robot, TCS Res & Innovat, Bombay, Maharashtra, India
[2] Tampere Univ Technol, Tampere, Finland
关键词
Cognitive load; Confidence level; Eye tracking; Pupil size; EMD; EEMD; VMD; ICA; EMPIRICAL-MODE DECOMPOSITION; WORKLOAD;
D O I
10.1016/j.cogsys.2018.07.021
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Spontaneous pupillary fluctuations are indicative of the cognitive load imposed while doing a task involving memory resources. However, the fluctuations are also dependent on other factors like lighting conditions, uncertainty or the level of confidence while performing the task and so on. This paper aims to separate various components of pupillary response in order to assess the cognitive load and the confidence with which the task is performed. Hybrid decomposition models using ensemble empirical mode decomposition followed by independent component analysis is found to effectively reconstruct the original signal. The variational Mode Decomposition has been used in order to overcome the limitations imposed by empirical mode decomposition. Results show that variational mode decomposition outperforms existing state-of-the-art methods. Further, we attempted to identify the hidden components of pupillary response during cognitive tasks like mental addition and the anagram test. We obtained F-score of 0.67 in the detection of cognitive load and F-score of 0.99 for the detection of confidence level from the single channel pupil data. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码:325 / 334
页数:10
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