Noninvasive prediction of Blood Lactate through a machine learning-based approach.

ABSTRACT: We hypothesized that blood lactate concentration([Lac]_blood) is a function of cardiopulmonary variables, exercise intensity and some anthropometric elements during aerobic exercise. This investigation aimed to establish a mathematical model to estimate [Lac]_blood noninvasively during constant work rate (CWR) exercise of various intensities. 31 healthy participants were recruited and each underwent 4 cardiopulmonary exercise tests: one incremental and three CWR tests (low: 35% of peak work rate for 15 min, moderate: 60% 10 min and high: 90% 4 min). At the end of each CWR test, venous blood was sampled to determine [Lac]_blood. 31 trios of CWR tests were employed to construct the mathematical model, which utilized exponential regression combined with Taylor ex

SUBMITTER: Huang SC 

PROVIDER: S-EPMC6379358 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature