Key result
Pilot experience is linked to greater physiological sample entropy increases during emergency flight transitions.
Why the study?
Whether nonlinear, time-frequency, directional, change-point, and visibility graph measures characterize physiological reorganization during real-flight operational transitions and whether the observed patterns differ by flight experience was uncertain.
Do nonlinear, time-frequency, directional, change-point, and visibility graph measures of physiological reorganization during real-flight operational transitions differ by flight experience in male pilots?
Observational (n=12)
Do nonlinear, time-frequency, directional, change-point, and visibility graph measures of physiological reorganization during real-flight operational transitions differ by flight experience in male pilots?
Multi-scale network and nonlinear physiological analyses during real-flight scenarios can characterize autonomic reorganization and differentiate between experienced and non-experienced pilots during emergency conditions.
Answers are grounded in this paper and cite their sources.
Exploratory metrics may detect physiological shifts in pilots; leaves open validation for operational monitoring or experience stratification.
Purpose: This exploratory study examined whether nonlinear, time-frequency, directional, change-point, and visibility graph measures characterize physiological reorganization during real-flight operational transitions and whether the observed patterns differ by flight experience. Methods: Heart rate variability (HRV), respiration, skin temperature, and movement were recorded from twelve male pilots, comprising six experienced and six non-experienced participants, during resting (REST), normal-flight (NOR), and emergency-failure (EF) conditions. Sample entropy (SampEn), approximate entropy (ApEn), detrended fluctuation analysis (DFA), recurrence quantification analysis (RQA), continuous wavelet transform (CWT), segment-level classification, Granger-predictive modelling, cumulative sum (CUSUM), Bayesian change-point detection, and natural visibility graph (NVG) and horizontal visibility graph (HVG) analyses were applied. Results: In the pooled series for each cohort and condition, SampEn increased from REST to EF from 0.8412 to 1.7918 in the experienced group and from 0.8294 to 1.4251 in the non-experienced group. DFA α1 increased from 0.5418 to 1.4872 in the experienced group and from 0.5102 to 1.0621 in the non-experienced group. Recurrence rate declined from 0.3223 to 0.2428 in the experienced group and from 0.3058 to 0.2344 in the non-experienced group. EF scalograms showed a broader, visually V-shaped energy envelope over scale. The classification analysis was treated as an exploratory assessment of discrimination among the 71 analyzed windows. In the cohort-level directional networks, respiratory-to-cardiac links remained visible across the experienced-group conditions, whereas fewer such links were present in the non-experienced EF network than in its REST network. Bayesian posterior peaks occurred near scenario transition indices 12 and 34. NVG density was lower in EF than in REST in the experienced group (0.3333 vs. 0.1283) and the non-experienced group (0.4091 vs. 0.1247). Conclusion: The coordinated analysis characterized condition-related physiological patterns across complementary system representations and described experience-related differences within the study cohort.
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Alharasees et al. (2026) conducted an observational in Physiological reorganization and resilience during real-flight operational transitions (n=12). Experienced pilot status during real-flight operational transitions (resting, normal-flight, and emergency-failure) vs. Non-experienced pilots was evaluated on Physiological reorganization across resting (REST) to emergency-failure (EF) transitions (including sample entropy [SampEn], detrended fluctuation analysis [DFA α1], recurrence rate, and visibility graph density). Experienced pilots showed larger sample entropy increases from rest to emergency flight (0.8412 to 1.7918) than non-experienced pilots (0.8294 to 1.4251).
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