Personal Statistics-Based Heart Rate Evaluation Using Interval Type-2 Fuzzy Sets

In today's health-conscious world, patient monitoring is increasingly emphasized both in science and in everyday life. For this reason, personalized, reliable evaluation has been in the focus of science in recent years. In this paper, a fuzzy-based system is presented that can handle blurred boundaries when evaluating physiological values. In order to ensure a personalized evaluation in the model, it takes into account statistics prepared from values measured under identical or nearly identical conditions. The essence of the proposed method is to modify the normal range determined on the basis of medical recommendations by the patient's usual reactions. As a consequence of this modification an even more personalized and realistic result can be generated. This modification is based on the use of interval type-2 fuzzy sets to handle the uncertainty arising from the discrepancy between the doctor's recommendation and the patient's normal reactions.