Background Hypertension is a kind of clinical syndrome, characterized by the increase of systemic arterial pressure. There is a lack of identifiable triggers and predictors of hypertensive disease in response to treatment at rest and during exercise. In this study, a mathematical model was used to screen and compare the indicators and related changes at rest and during exercise between normotensive and hypertensive individuals. Methods Blood pressure and ultrasound-related indicators, blood biochemical indicators and metabolic compounds were collected and logistic regression model and Principal component analysis (PCA) were used to explore the differences of indexes at rest and in different exercise states in healthy and hypertensive patients. An indicator change map for hypertension is established. Results The results reveal that hypertension is not only related to oxidative stress, inflammatory reaction and fatty acid oxidation, but also involves various amino acid metabolism. The defined mathematical models and indicators changes during exercise might be helpful for early screening of hypertension and future studies are needed to explore their value on prevention and control of hypertension. Conclusion The research shows that the main regulation indicators at different exercise states differ significantly in the normal group and the hypertensive group. The key indicators of the normal group are blood pressure and ultrasound related indicators, while those of the hypertensive group are metabolites related to lactic acid metabolism, glycolysis, aerobic oxidation and lipid metabolism.