This work presents the development of a simulation tool, designed to study the impact of physical activity and lifestyle on the health of young adults. The implemented solution produces synthetic physiological signals, such as ECG, EDA, and skin temperature, based on personalised profiles provided by the user. The system integrates a specific regression model for each bi-osignal, geographical route simulation, and interactive visualisations that en-able contextualised analysis of physiological and emotional patterns. The tool was designed to support teaching, prototyping, and research activities in biomedicine. The results were represented in time graphs and interactive maps, allowing observation of the evolution of the signals along the simulat-ed paths. The validity of the signals produced was confirmed through model performance tests, with metrics such as the coefficient of determination (R2) and the root mean square error (RMSE). The results obtained reinforce the physiological plausibility of the simulated signals and the applicability of the system in real digital health contexts.