From Heart Rate Variability to Adaptive Physiological Reconfiguration: A Multisystem Hypothesis of Health and Disease

Clinical assessment commonly relies on physiological variables interpreted as isolated values or against population-derived thresholds. Although indispensable, these approaches provide limited information about regulatory flexibility, inter-system coordination, and recovery after stress. Physiological signals contain structured fluctuations across multiple temporal scales that reflect dynamic regulation and interactions among organ systems. This article proposes adaptive physiological reconfiguration as an integrative framework for interpreting disease-related changes in physiological dynamics. We hypothesize that disease-related vulnerability is associated with a reduced capacity of physiological systems to reconfigure signal dynamics and inter-system relationships appropriately across changing functional states and to restore a context-appropriate organization after perturbation. Heart rate variability provides a conceptual starting point, while network physiology extends this perspective toward multisystem regulation. Continuous multimodal monitoring and artificial intelligence may support the characterization of these dynamics but cannot establish causality. The framework generates testable predictions: dynamic and multisystem features should provide reproducible information beyond corresponding mean values and isolated signals, while recovery trajectories should help characterize physiological resilience. These hypotheses require standardized measurement, external validation, and prospective evaluation.