Izvestiya of Saratov University.

Physics

ISSN 1817-3020 (Print)
ISSN 2542-193X (Online)

For citation:

Dubinkina E. S., Karavaev A. S., Frolova S. V., Lazunina E. A., Zinchenko E. M., Burmistrov S. E., Bezruchko B. P., Borovkova E. I. Comparative analysis of the sensitivity of physiological markers of cognitive load. Izvestiya of Saratov University. Physics , 2026, vol. 26, iss. 3, pp. 295-304. DOI: 10.18500/1817-3020-2026-26-3-295-304, EDN: NCIVHT

This is an open access article distributed under the terms of Creative Commons Attribution 4.0 International License (CC-BY 4.0).
Published online: 
30.09.2026
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Language: 
Russian
Heading: 
Biophysics and medical physics
Article type: 
Article
UDC: 
530.182:537.86
DOI: 
10.18500/1817-3020-2026-26-3-295-304
EDN: 
NCIVHT

Comparative analysis of the sensitivity of physiological markers of cognitive load

Autors: 
Dubinkina Elizaveta S., Saratov State University
Karavaev Anatoly Sergeevich, Saratov State University
Frolova Svetlana V., Saratov State University
Lazunina Ekaterina Alekseevna, Saratov State University
Zinchenko Ekaterina M., Saratov State University
Burmistrov Sergey E., Saratov State University
Bezruchko Boris Petrovich, Saratov State University
Borovkova Ekaterina Igorevna, Saratov State University
Abstract: 

Background and Objectives: Physiological indices are widely used for non-invasive assessment of cognitive load, but the sensitivity of various indices remains poorly understood. This study compares the sensitivity of a set of physiological indices available for recording by wearable devices to changes in cognitive load. Materials and Methods: Seventy healthy men were examined for electrocardiogram, photoplethysmogram, respiration, electromyogram, galvanic skin response, and extremity temperature at rest and during a mental arithmetic test. Four heart rate variability indices were calculated from the electrocardiogram; perfusion index and pulse rate were calculated from the photoplethysmogram; and respiratory rate was calculated from the respiratory signal spectrum. Results: The most sensitive indices were the high-frequency component of heart rate variability, the standard deviation of RR intervals, the stress index, and the perfusion index, the latter of which was used for the first time to diagnose cognitive load. A comparison of the experimental distribution of the number of simultaneously occurring indicators with a binomial model has revealed significant differences, indicating a systemic rather than independent nature of the physiological response. Conclusion: The four most sensitive indices can be calculated from a single photoplethysmogram signal, which justifies the development of compact wearable devices for monitoring cognitive load in everyday settings.

Key words: 
cognitive load
physiological indices
heart rate variability
perfusion index
Acknowledgments: 
This work was supported by the Russian Science Foundation (project No. 25-12-00181, https://rscf.ru/project/25-12-00181/).
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Received: 
13.04.2026
Accepted: 
17.06.2026
Published: 
30.09.2026
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