https://doi.org/10.1140/epjs/s11734-026-02187-0
Review
Neurocardiac diving reflex dynamics: assessment and prediction
1
Department of Neurophysiology, Neuropsychology and Neuroinformatics, Medical University of Gdańsk, Tuwima Str. 15, 80-210, Gdansk, Poland
2
Department of Biostatistics and Biomedical Systems Theory, Ludwik Rydygier Collegium Medicum in Bydgoszcz Nicolaus Copernicus University, Toruń, Poland
a
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Received:
13
October
2025
Accepted:
3
February
2026
Published online:
16
February
2026
Abstract
The diving reflex is an adaptive response characterized by autonomic co-activation, which optimizes oxygen conservation through bradycardia and vasoconstriction. While functional, it poses risks of life-threatening arrhythmias. Due to significant inter-individual variability, developing reliable models to predict individual cardiodepressive responses is crucial for clinical and occupational safety. This study develops predictive models by integrating resting autonomic profiles with an assessment of the breath-hold diving-induced reaction. The methodology follows a two-stage approach. First, basal cardiac activity is characterized using standard Heart Rate Variability (HRV) and resting Heart Rate (HR) metrics to establish independent variables. Second, the neuro-cardiac response is quantified through exponential modeling of bradycardia kinetics (time constant τ) and time–frequency HRV. In addition, symbolic analysis and fractal parameters are employed to capture the non-linear complexity of the response and the phenomenon of autonomic co-activation. The final stage of the work involves synthesizing the obtained parameters into predictive models of increasing complexity by linking resting autonomic indices with the HR deceleration during diving reflex via both classical correlation analyses and advanced machine learning (ML) algorithms.
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© The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2026
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
