TUTCRIS - Tampereen teknillinen yliopisto

TUTCRIS

Cognitive load and metacognitive confidence extraction from pupillary response

Tutkimustuotosvertaisarvioitu

Standard

Cognitive load and metacognitive confidence extraction from pupillary response. / Gavas, Rahul D.; Tripathy, Soumya Ranjan; Chatterjee, Debatri; Sinha, Aniruddha.

julkaisussa: Cognitive Systems Research, Vuosikerta 52, 01.12.2018, s. 325-334.

Tutkimustuotosvertaisarvioitu

Harvard

Gavas, RD, Tripathy, SR, Chatterjee, D & Sinha, A 2018, 'Cognitive load and metacognitive confidence extraction from pupillary response', Cognitive Systems Research, Vuosikerta. 52, Sivut 325-334. https://doi.org/10.1016/j.cogsys.2018.07.021

APA

Gavas, R. D., Tripathy, S. R., Chatterjee, D., & Sinha, A. (2018). Cognitive load and metacognitive confidence extraction from pupillary response. Cognitive Systems Research, 52, 325-334. https://doi.org/10.1016/j.cogsys.2018.07.021

Vancouver

Author

Gavas, Rahul D. ; Tripathy, Soumya Ranjan ; Chatterjee, Debatri ; Sinha, Aniruddha. / Cognitive load and metacognitive confidence extraction from pupillary response. Julkaisussa: Cognitive Systems Research. 2018 ; Vuosikerta 52. Sivut 325-334.

Bibtex - Lataa

@article{5915f13c59404e6ca5673623e33e5774,
title = "Cognitive load and metacognitive confidence extraction from pupillary response",
abstract = "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 Fscore of 0.67 in the detection of cognitive load and Fscore of 0.99 for the detection of confidence level from the single channel pupil data.",
keywords = "Cognitive load, Confidence level, EEMD, EMD, Eye tracking, ICA, Pupil size, VMD",
author = "Gavas, {Rahul D.} and Tripathy, {Soumya Ranjan} and Debatri Chatterjee and Aniruddha Sinha",
year = "2018",
month = "12",
day = "1",
doi = "10.1016/j.cogsys.2018.07.021",
language = "English",
volume = "52",
pages = "325--334",
journal = "Cognitive Systems Research",
issn = "1389-0417",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) - Lataa

TY - JOUR

T1 - Cognitive load and metacognitive confidence extraction from pupillary response

AU - Gavas, Rahul D.

AU - Tripathy, Soumya Ranjan

AU - Chatterjee, Debatri

AU - Sinha, Aniruddha

PY - 2018/12/1

Y1 - 2018/12/1

N2 - 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 Fscore of 0.67 in the detection of cognitive load and Fscore of 0.99 for the detection of confidence level from the single channel pupil data.

AB - 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 Fscore of 0.67 in the detection of cognitive load and Fscore of 0.99 for the detection of confidence level from the single channel pupil data.

KW - Cognitive load

KW - Confidence level

KW - EEMD

KW - EMD

KW - Eye tracking

KW - ICA

KW - Pupil size

KW - VMD

U2 - 10.1016/j.cogsys.2018.07.021

DO - 10.1016/j.cogsys.2018.07.021

M3 - Article

VL - 52

SP - 325

EP - 334

JO - Cognitive Systems Research

JF - Cognitive Systems Research

SN - 1389-0417

ER -