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Beyond traditional approaches: a partial directed coherence with graph theory-based mental load assessment using EEG modality

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Abstract

Brain connectivity-based methods are efficient and reliable for assessing the mental workload during high task demands as the human brain is functionally interconnected during any psychological task. On the other hand, the graph theory approach is a mathematical study that draws the pairwise relationships between objects. This paper covers the deployment of graph theory concepts on the brain connectivity methods to find the complex underlying behaviors of the brain in the simplest way. Furthermore, in this work, mental workload assessments on multimedia animations were performed using a brain connectivity approach based on partial directed coherence (PDC) with graph theory analysis. Electroencephalography (EEG) data were collected from 34 adult participants at baseline and during multimedia learning tasks. The results revealed that the EEG-based connectivity approach with graph theory offers more promising results than the traditional feature extraction techniques. The connectivity approach achieved an accuracy of 85.77% in comparison with the 78.50% accuracy achieved by the existing feature extraction techniques. It is concluded that the proposed PDC method with graph theory network analysis is a better solution for cognitive load assessment during any cognitive task.

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Acknowledgements

This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, under grant No. DF-129-611-1441. The authors, therefore, gratefully acknowledge DSR for technical and financial support.

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Authors and Affiliations

  1. Centre for Intelligent Signal and Imaging Research (CISIR), Department of Electrical & Electronic Engineering, Universiti Teknologi PETRONAS, Perak, Malaysia

    Moona Mazher

  2. Department of Information & Engineering, ImViA Laboratory, University of Burgundy, Dijon, France

    Abdul Qayyum

  3. Department of Computer Science, Mohi-ud-Din Islamic University, Nerian Sharif, AJ&K, 10250, Pakistan

    Iftikhar Ahmad

  4. Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Madini O. Alassafi

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  1. Moona Mazher
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  2. Abdul Qayyum
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  4. Madini O. Alassafi
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Correspondence to Abdul Qayyum.

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Mazher, M., Qayyum, A., Ahmad, I. et al. Beyond traditional approaches: a partial directed coherence with graph theory-based mental load assessment using EEG modality. Neural Comput & Applic 34, 11395–11410 (2022). https://doi.org/10.1007/s00521-020-05408-2

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