Exercise monitoring from a Network Physiology approach

Advancements in big data, artificial intelligence and related technology are shaping the future of exercise monitoring, yet current monitoring strategies may not fully capture the physiological complexity of athletes’ health and performance. The multidisciplinary field of Network Physiology provides a conceptual and analytical framework to investigate the dynamic interactions, coordination and network integration among physiological systems in athletes during exercise, and thus, opens new directions in Exercise Physiology. This article aims to summarize the current advances, vision and perspectives within this framework, focusing on how investigations of the inter-organ dynamic networks (cardio-respiratory, cardio-muscular, cortico-cardiac, cortico-muscular, inter-muscular, etc.) can lead to valuable insights into athletes’ performance, exercise monitoring, the underlying regulatory mechanisms of systems adaptation and coordination in response to exercise-induced stress, and to identify a novel class of network-based biomarkers related to training, levels of fitness, fatigue, and recovery.