Personal-Statistics-Based Heart Rate Evaluation in Anytime Risk Calculation Model

Nowadays, the changes in people's habits and the development of technology result in the wide spreading of the model-based health monitoring systems. In this paper, an improvement of the measurement evaluation method is introduced, which is used during the sport activity in real-time. The basis of the novel approach is our previously reported anytime hierarchical fuzzy risk calculation model, which is able to handle some uncertainties, imprecision, and subjectivity in the data and in the evaluation process and can cope with the dynamically changing environment, available time, and resources. In the new model the input membership functions, which are tuned according to the patient characteristics, are modified based on the data recorded during previous measurements under the same conditions. By this, the person-dependent characteristics and the unavoidable changing of the dynamic reactions of the human organism can also be considered and the risk level can be more reliably predicted.