Health monitoringHealth monitoring playsRisk assessment a crucial role for those involved in sports and physical activities, as each individual presents unique physiological responses under varying physical loads. Traditional health assessment methods, however, often fall short in taking this difference in individual response into account, emphasizing the need for more personalized approaches. This paper introduces a hierarchical fuzzy model designed to evaluate the risk levels associated with physical activities. Using a personal statistics-based approach to fine-tune membership functions, the model effectively personalizes evaluations to better reflect individual health profiles. The model shows both numerical and linguistic assessments of risk, demonstrating a significant correlation between the improved membership functions and the existing medical recommendations. This study not only showcases the potential of fuzzy logicFuzzy logic in improving health monitoringHealth monitoring but also lays important groundwork for future research focused on developing innovative mathematical methods to represent patient statistics and refine membership function fitting.