Unsupervised approach for measurement of cognitive load using EEG signals

Das, Dhiman; Chatterjee, Debatri; Sinha, Aniruddha

doi:10.1109/bibe.2013.6701686

Cited by 19 publications

(13 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Earlier research work [8] used the Stroop test as reference to evaluate the performance of logical reasoning task and usability of on-screen keyboard layouts. The objective of the present research is to find the validity of a reference stimulus for a given unknown stimulus.…”

Section: Proposed Methodologymentioning

confidence: 99%

“…In this test, we have used two sets of logical reasoning questions as explained in [8]. Two sets are designed based on rules of propositional logic to introduce two different levels of cognitive loads.…”

Section: B Logical Reasoning Testmentioning

confidence: 99%

“…These were previously used by Das et al [8] with the objective of testing the logical reasoning skills and evaluation of the on-screen keyboard layouts using a training model based on Stroop test. The objective of the present study is to verify the validity of their approach.…”

Section: Introductionmentioning

confidence: 99%

“…In order to answer these questions we have selected three types of diversified stimulus namely Stroop color test [7], logical reasoning test [8] and usability of two different onscreen keyboard layouts [9]. These were previously used by Das et al [8] with the objective of testing the logical reasoning skills and evaluation of the on-screen keyboard layouts using a training model based on Stroop test.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Validation of stimulus for EEG signal based cognitive load analysis

Sinha

Chatterjee

Saha

et al. 2015

2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)

Self Cite

View full text Add to dashboard Cite

Cognitive load is defined as the mental workload imparted on brain while doing a task. The amount of cognitive load experienced depends on individual's ability of perception, assimilation and response to a task. Real-time measurement of the level of cognitive load using low cost Electroencephalogram (EEG) signal enables understanding of personal cognitive skills. In this paper, we propose a methodology of selecting a reference task whose bio-markers closely match with a given task while probing different cognitive abilities. The benefit of this approach is to have a limited set of training models for the reference tasks related to various cognitive categories and use the same for a variety of unknown tasks. Experiment is performed for two levels of cognitive load with three different tasks namely Stroop color task, logical reasoning task and usage of on-screen keyboards. The training models of the reference tasks, selected by cluster analysis of low and high cognitive levels are used to evaluate an unknown task. Experimental results indicate that the Stroop is a better reference for On-Screen keyboard test compared to the Logical reasoning test. Support vector machine (SVM) and principal component analysis (PCA) followed by SVM (PCA-SVM) are used as the classifiers for the testing.

show abstract

Section: Proposed Methodologymentioning

confidence: 99%

Section: B Logical Reasoning Testmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Validation of stimulus for EEG signal based cognitive load analysis

Sinha

Chatterjee

Saha

et al. 2015

2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)

Self Cite

View full text Add to dashboard Cite

show abstract

“…Ledger's [46] experiments showed that blink rate decreases as cognitive load increases. Das et al [47] …”

Section: Physiological Measuresmentioning

confidence: 97%

The State-of-The-Art

Chen¹,

Zhou²,

Wang³

et al. 2016

Robust Multimodal Cognitive Load Measurement

View full text Add to dashboard Cite

Recent years have witnessed booming growth in the research of cognitive load understanding and measurement [1]. Extensive research has been carried out into cognitive load theory, cognitive load measurement, applications of cognitive load theory, and the factors that may affect cognitive load. This chapter surveys the state-of-the-art of cognitive load measurement and gives an overview of current research in cognitive load measurement. The highlights include:

show abstract

P300 Brain Waves Instigated Semi Supervised Video Surveillance for Inclusive Security Systems

Singh

Jotheeswaran

2018

Advances in Brain Inspired Cognitive Systems

View full text Add to dashboard Cite

Unsupervised approach for measurement of cognitive load using EEG signals

Cited by 19 publications

References 29 publications

Validation of stimulus for EEG signal based cognitive load analysis

Validation of stimulus for EEG signal based cognitive load analysis

The State-of-The-Art

P300 Brain Waves Instigated Semi Supervised Video Surveillance for Inclusive Security Systems

Contact Info

Product

Resources

About