ArticleBehavior research methods2025
Reliability and reactivity of heart rate variability and pupillometry in response to controlled autonomic perturbations in university students.
Article in Behavior research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Heart Rate Variability and Body Motion as Digital Biomarkers of Task Workload During Military En Route Critical Care Simulations.Sensors (Basel, Switzerland) · 2026Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of this test-retest reliability study was to evaluate the reliability and reactivity of heart rate variability (HRV) and pupillometry metrics under conditions with controlled cognitive stimulation and paced breathing within a virtual reality protocol. After habituation, 30 English-speaking university students completed a four-phase protocol on two occasions separated by 1 week. HRV and pupillometry were continuously measured during the following phases: baseline, cognitive testing, guided breathing with nature immersion, and spontaneous breathing with nature immersion. Strong day-to-day relative reliability was confirmed for both HRV (pooled ICC: 0.75 to 0.83) and pupillometry (pooled ICC: 0.66 to 0.87). HRV metrics of sympathovagal balance in the time, frequency, and non-linear domains showed reactivity with significant differences between all phases. Pupillometry metrics increased progressively from cognitive testing to guided breathing nature immersion to nature immersion, suggesting psychological rather than respiratory influences. Relatively large minimal detectable change values were determined across HRV (22 to 54% deviation from baseline) and pupillometry (33 to 88% deviation from baseline) metrics. Although the relatively large ratio limits of agreement and minimal detectable change values suggest that detecting systematic changes in these metrics over time might be difficult at the individual level, strong relative reliability supports the use of HRV and pupillometry metrics to detect differences in sympathovagal balance between groups. Additionally, the responsiveness of these metrics demonstrates the efficacy of the proposed virtual reality protocol in inducing detectable physiological reactivity across HRV and pupillometry metrics.
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