Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals
Human cognitive load level assessment is a challenging issue in the field of functional brain imaging. This work aims to study different cognitive load levels statistically from brain hemodynamics. Since the functional brain activities can be evaluated by functional near-infrared spectroscopy (fNIRS...
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| Format: | Article |
| Language: | English |
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Elsevier
2022-09-01
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| Series: | Neuroscience Informatics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772528622000048 |
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| author | Farzana Khanam A.B.M. Aowlad Hossain Mohiuddin Ahmad |
| author_facet | Farzana Khanam A.B.M. Aowlad Hossain Mohiuddin Ahmad |
| author_sort | Farzana Khanam |
| collection | DOAJ |
| description | Human cognitive load level assessment is a challenging issue in the field of functional brain imaging. This work aims to study different cognitive load levels statistically from brain hemodynamics. Since the functional brain activities can be evaluated by functional near-infrared spectroscopy (fNIRS), a renowned fNIRS dataset is considered for this work. The dataset contains fNIRS data of three types of n-back tasks (0-back, 2-back, and 3-back) of twenty-six healthy volunteers. The fNIRS signals were pre-processed and separated according to the tasks and trials. The mean changes of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (dHb) are calculated from each trial corresponding to the tasks and tested for significant inference among three levels utilizing analysis of variance (ANOVA). From the outcomes of the ANOVA (p<0.005), two significant channels (AF7 (frontal) and C3h (motor)) were figured out. The significance of these two channels was further justified using the property consistency test by three different time intervals of hemodynamics inside the total task period. The latter result also explored the functional pattern of the hemodynamics of AF7 and C3h positions. Moreover, two-level cognitive load (due to easy i.e., 0-back test and hard i.e., 2-back and 3-back task) is classified using support vector machine and found classification accuracy in average 73.40%±0.076 for HbO2 data and 71.48%±0.061 for dHb data. The study signposts the collective role played by both fNIRS signals and statistical valuation of functioning cognitive load efficacy to use fNIRS as a cognitive load assessment biomarker. |
| first_indexed | 2024-04-13T02:13:07Z |
| format | Article |
| id | doaj.art-ced5af4881484a9ab3d0fae791dbfb68 |
| institution | Directory Open Access Journal |
| issn | 2772-5286 |
| language | English |
| last_indexed | 2024-04-13T02:13:07Z |
| publishDate | 2022-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neuroscience Informatics |
| spelling | doaj.art-ced5af4881484a9ab3d0fae791dbfb682022-12-22T03:07:15ZengElsevierNeuroscience Informatics2772-52862022-09-0123100042Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signalsFarzana Khanam0A.B.M. Aowlad Hossain1Mohiuddin Ahmad2Department of Biomedical Engineering, Khulna University of Engineering & Technology (KUET), Khulna-9203, Bangladesh; Corresponding author.Department of Electronics and Communication Engineering, Khulna University of Engineering & Technology (KUET), Khulna-9203, BangladeshDepartment of Electrical and Electronic Engineering, Khulna University of Engineering & Technology (KUET), Khulna-9203, BangladeshHuman cognitive load level assessment is a challenging issue in the field of functional brain imaging. This work aims to study different cognitive load levels statistically from brain hemodynamics. Since the functional brain activities can be evaluated by functional near-infrared spectroscopy (fNIRS), a renowned fNIRS dataset is considered for this work. The dataset contains fNIRS data of three types of n-back tasks (0-back, 2-back, and 3-back) of twenty-six healthy volunteers. The fNIRS signals were pre-processed and separated according to the tasks and trials. The mean changes of oxygenated hemoglobin (HbO2) and deoxygenated hemoglobin (dHb) are calculated from each trial corresponding to the tasks and tested for significant inference among three levels utilizing analysis of variance (ANOVA). From the outcomes of the ANOVA (p<0.005), two significant channels (AF7 (frontal) and C3h (motor)) were figured out. The significance of these two channels was further justified using the property consistency test by three different time intervals of hemodynamics inside the total task period. The latter result also explored the functional pattern of the hemodynamics of AF7 and C3h positions. Moreover, two-level cognitive load (due to easy i.e., 0-back test and hard i.e., 2-back and 3-back task) is classified using support vector machine and found classification accuracy in average 73.40%±0.076 for HbO2 data and 71.48%±0.061 for dHb data. The study signposts the collective role played by both fNIRS signals and statistical valuation of functioning cognitive load efficacy to use fNIRS as a cognitive load assessment biomarker.http://www.sciencedirect.com/science/article/pii/S2772528622000048Functional near-infrared spectroscopy (fNIRS)HemodynamicsCognitive loadn-back testANOVA testGrand average |
| spellingShingle | Farzana Khanam A.B.M. Aowlad Hossain Mohiuddin Ahmad Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals Neuroscience Informatics Functional near-infrared spectroscopy (fNIRS) Hemodynamics Cognitive load n-back test ANOVA test Grand average |
| title | Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals |
| title_full | Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals |
| title_fullStr | Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals |
| title_full_unstemmed | Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals |
| title_short | Statistical valuation of cognitive load level hemodynamics from functional near-infrared spectroscopy signals |
| title_sort | statistical valuation of cognitive load level hemodynamics from functional near infrared spectroscopy signals |
| topic | Functional near-infrared spectroscopy (fNIRS) Hemodynamics Cognitive load n-back test ANOVA test Grand average |
| url | http://www.sciencedirect.com/science/article/pii/S2772528622000048 |
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