Premenstrual Syndrome Detection Based on Granular Computing and AI in Home Environment

Premenstrual syndrome affects women’s daily functioning in various ways. The designed algorithm applied into mobile application is intended to support women’s health by enabling a better understanding of the processes occurring in their bodies during the cycle and detecting the pattern with specific symptoms groups appearing cyclically. The input data comes from an application that collects information about the woman’s health and symptoms. The AI algorithm determines the Information Granules and then analyzes them in terms of intensity and frequency of various symptom combinations. Ultimately determines the level of risk of PMS.