Relationship between maximal aerobic power with aerobic fitness as a function of signal-to-noise ratio.

Efforts to better understand cardiorespiratory health are relevant for the future development of optimized physical activity programs. We aimed to explore the impact of the signal quality on the expected associations between the ability of the aerobic system in supplying energy as fast as possible during moderate exercise transitions with its maximum capacity to supply energy during maximal exertion. It was hypothesized that a slower aerobic system response during moderate exercise transitions is associated with a lower maximal aerobic power; however, this relationship relies on the quality of the oxygen uptake data set. Forty-three apparently healthy participants performed a moderate constant work rate (CWR) followed by a pseudorandom binary sequence (PRBS) exercise protocol on a cycle ergometer. Participants also performed a maximum incremental cardiopulmonary exercise testing (CPET). The maximal aerobic power was evaluated by the peak oxygen uptake during the CPET, and the aerobic fitness was estimated from different approaches for oxygen uptake dynamics analysis during the CWR and PRBS protocols at different levels of signal-to-noise ratio. The product moment correlation coefficient was used to evaluate the correlation level between variables. Aerobic fitness was correlated with maximum aerobic power, but this correlation increased as a function of the signal-to-noise ratio. Aerobic fitness is related to maximal aerobic power; however, this association appeared to be highly dependent on the data quality and analysis for aerobic fitness evaluation. Our results show that simpler moderate exercise protocols might be as good as maximal exertion exercise protocols to obtain indexes related to cardiorespiratory health.NEW & NOTEWORTHY Optimized methods for cardiorespiratory health evaluation are of great interest for public health. Moderate exercise protocols might be as good as maximum exertion exercise protocols to evaluate cardiorespiratory health. Pseudorandom or constant workload moderate exercise can be used to evaluate cardiorespiratory health.

A phenomenology model of normal sinus rhythm in healthy humans.

The fractal component in the daytime healthy heartbeat interval data is studied from the perspective of cascade in fluid turbulence. Based on the electrophysiology of the heart muscle cell, a bounded random cascade model is assumed and the scaling property of the model is derived. In application, a "cascade decomposition" is proposed to extract the model parameter based on the experimental data. Simulation results show that healthy heart rate variability (HRV) can be well captured by the multiplicative process and imply the significance of sympatho-vagal interaction in the fractal component of long-term healthy HRV.