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International Conference on Applied Human Factors and Ergonomics

AHFE 2020: Advances in Neuroergonomics and Cognitive Engineering pp 319–325Cite as

Investigation of EEG Correlate in NIRS Signal for BCI

Part of the Advances in Intelligent Systems and Computing book series (AISC,volume 1201)

Abstract

In this study, a unique approach has been presented for performing correlation between the signals of two neuroimaging modalities for motor imagery data. By correlating the signals, we investigate the time sequence relationship between the haemodynamic response and electrophysiological activity during the performance of mental arithmetic vs resting-state and motor imagery activity of right vs left hand, as we correlate near-infrared spectroscopy (NIRS) and electroencephalography (EEG) signals respectively obtained during the same activity. Data of both EEG and NIRS are taken from “Open Access Dataset for EEG+NIRS Single-Trial Classification”. Thirty active electrodes have been used for the EEG data extraction using 1000 Hz as the sampling frequency. International 10-5 system has been employed for electrode placement for EEG signal extraction and one-tailed Pearson’s correlation analysis has been exercised on the responses of prominent channels. By correlating the EEG-NIRS signals, we demonstrate the correlation between haemodynamic response and readiness potential (RP) in the premotor cortex. Both modalities are also used for Mental Workload assessment so our work proves helpful in MWL results extraction too. The suggested correlation method can be utilized for approach validation procedures in future multi-modal BCI research activities.

Keywords

  • Correlation
  • Electrode
  • Electrophysiological
  • Haemodynamic
  • Mental Workload assessment
  • Neuroimaging modalities

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Acknowledgments

We would like to acknowledge School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), Pakistan and European Union (EU)’s Horizon 2020, Research and Innovation Staff Exchange Evaluations (RISE) under grant agreement No 823904 - ENHANCE project (MSCA-RISE 823904) for technical support and funding.

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Authors and Affiliations

  1. Department of Robotics and Intelligent Machine Engineering, National University of Sciences and Technology (NUST), H-12, Islamabad, 44000, Pakistan

    Ahmed Husnain Johar, Talha Yousaf, Umer Asgher, Yasar Ayaz, Muhammad Jawad Khan, Lala Mustafa & Khurram Khalil

  2. Department of Maritime Operations, University of South-Eastern Norway, Postboks 4, 3199, Borre, Norway

    Salman Nazir

Authors
  1. Ahmed Husnain Johar
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  2. Talha Yousaf
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  4. Yasar Ayaz
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  5. Salman Nazir
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  6. Muhammad Jawad Khan
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Correspondence to Ahmed Husnain Johar .

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Editors and Affiliations

  1. Drexel University, Philadelphia, PA, USA

    Dr. Hasan Ayaz

  2. National University of Sciences and Tech (NUST), School of Mech and Manufacturing Eng (SMME), Islamabad, Pakistan

    Umer Asgher

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Johar, A.H. et al. (2021). Investigation of EEG Correlate in NIRS Signal for BCI. In: Ayaz, H., Asgher, U. (eds) Advances in Neuroergonomics and Cognitive Engineering. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1201. Springer, Cham. https://doi.org/10.1007/978-3-030-51041-1_42

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