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Detection of Cognitive Load Modulation by EDA and HRV.

Alexis Boffet1,2, Laurent M Arsac1, Vincent Ibanez2

  • 1Laboratoire IMS, CNRS, UMR 5218, Université de Bordeaux, Talence, France.

Sensors (Basel, Switzerland)
|April 26, 2025
PubMed
Summary

This study shows that combining electrodermal activity (EDA) and heart rate variability (HRV) markers, specifically EDATVSYMP and HF-HRVVFCDM, accurately predicts perceived cognitive load. This integrated approach offers a more reliable method for monitoring mental workload.

Keywords:
2-backEDAHRVNASA-TLXcognitive load

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Area of Science:

  • Physiology
  • Neuroscience
  • Human-Computer Interaction

Background:

  • Autonomic nervous system activity, measured via electrodermal activity (EDA) and heart rate variability (HRV), provides insights into cognitive processes.
  • Accurately quantifying cognitive load, a complex construct influenced by emotions, remains challenging using single biosignals.

Purpose of the Study:

  • To investigate the combined utility of EDA and HRV markers for assessing cognitive load during mental tasks.
  • To identify reliable biosignal-derived markers predictive of perceived cognitive load and mental workload.

Main Methods:

  • Participants underwent a two-back task and viewed emotional images while EDA and HRV were recorded.
  • HRV signals were analyzed using variable frequency complex demodulation (VFCDM) and wavelet packet transform (WPT).
  • EDA indices were extracted using VFCDM (EDATVSYMP), WPT (EDAWPT), and convex optimization (EDACVX).

Main Results:

  • Significant differences in cognitive load and emotional states were observed, correlating with EDACVX, EDATVSYMP, and HF-HRVVFCDM.
  • EDATVSYMP and HF-HRVVFCDM were identified as key predictors of the NASA-TLX cognitive load score.
  • K-means clustering revealed three distinct profiles of autonomic responses based on EDATVSYMP and HF-HRVVFCDM.

Conclusions:

  • Combining EDA and HRV markers offers a more comprehensive and accurate assessment of perceived cognitive load than single biosignals.
  • The identified EDATVSYMP and HF-HRVVFCDM markers are valuable for monitoring mental workload in operators.
  • Distinct autonomic response profiles highlight the complexity of cognitive load perception and the need for multi-modal biosignal analysis.