Leveraging RingConn Smart Ring for Monitoring Women’s Menstrual Health: A Pilot Study

Women’s health is an important area of global public health research, encompassing numerous physical, psychological, and social dimensions. Among these, monitoring the menstrual cycle is a key aspect of health management. Currently, the menstrual cycle prediction mainly uses the method of recording historical dates, which relies on the self-report of the user and is subjective. However, with the advent of intelligent wearable technology, menstrual monitoring methods based on physiological indicators provide a more scientific approach. In this paper, we utilized temperature data monitored by the RingConn Smart Ring for trend analysis and predicted the next menstrual date based on the observed temperature trends. Among the recruited subjects, the prediction accuracy within ±3 days was 92.55%, verifying the method’s effectiveness and accuracy. This study lays the foundation for further exploration of menstrual prediction based on skin body temperature in the future.