A distributed event-triggered framework for coordinating athlete autonomic states via wearable sensor networks.

Background: Interpersonal autonomic physiology (IAP) research has established that physiological synchrony (PS), the temporal interdependence of autonomic nervous system (ANS) activity across individuals, is an established phenomenon in team-based settings. However, PS in athlete cohorts has been studied exclusively as a passive observational variable; no framework actively regulates autonomic coherence under the communication constraints of wireless body area networks. This study integrates IAP and distributed control theory by formulating team-level autonomic coherence as a leaderless multi-agent consensus problem.

Methods: Each wearable unit was modeled as a two-dimensional linear agent whose state encodes cardiovascular autonomic tone (parasympathetic index: HRV-RMSSD) and sympathetic arousal load (EDA skin-conductance level, SCL), consistent with the Banister Fitness-Fatigue Model. Initial model states were derived from ECG/EDA records of WESAD subjects S2-S7, used only to provide heterogeneous simulation initial conditions (correlations were directional, non-significant sanity checks: r = -0.71, p = 0.114 for RMSSD; r = 0.68, p = 0.137 for SCL; N = 6). Three engineering challenges were addressed: (i) BLE communication delays h c ∈ [15, 150] ms; (ii) neuromuscular input delays h i ∈ [150, 300] ms; and (iii) switching directed topologies from dynamic team formations. A distributed dynamic event-triggered mechanism (DETM) drove all agents toward consensus while transmitting data only upon detection of meaningful state deviation. Stability was established via a dual-integral Lyapunov-Krasovskii functional, with LMI feasibility verified by CVXPY (ε = 0.087). Simulations ran for 300 s under three delay scenarios with five initial-condition perturbation folds; battery life was estimated from a four-component nRF52840 energy model.

Results: The proposed DETM reduced BLE transmissions by 38.38% in the nominal case while achieving convergence of the normalized model states within 4-7 s. A Zeno-free guarantee ( T min = 0.06 s) and a theoretical battery-life estimate of about 36 days were obtained. The ablation analysis attributed the largest communication saving to the dynamic internal variable ρ i ( t ) and the largest convergence-time improvement to the dual-delay structure. Five initial-condition perturbation folds indicated numerical robustness to the starting states.

Discussion: These

Findings: support control-theoretic and network-level feasibility only. Athlete studies are required before physiological benefits, safety, or real-world effectiveness can be inferred.