A Noninvasive Method for Dynamic Ovulation Monitoring Based on Memristor

The most common cause of female infertility is ovulatory disorders, accounting for approximately 57.5% of female infertility diagnoses, indicating that ovulation monitoring plays a pivotal role in fertility management. However, almost all of the current monitoring techniques face limitations in real-time accuracy and continuous data acquisition, hindering the development of reproductive medicine. In this work, it is first designed a noninvasive and real-time ovulation monitoring approach utilizing an Ag/HfO₂/FTO memristor by using HfO₂ as the functional layer of the device. By analyzing the I–V curve characteristics of saliva and urine samples across follicular, ovulatory, and luteal phases, it can be identified distinct peak current signatures with stable bipolar resistive switching over 100 cycles, which addresses critical limitations of current methods by offering noninvasive and real-time detection of the fertility window. Further, the as-proposed de novo theoretical mechanism is the modulation of the memristive switching behavior through hormone-driven ionic variations in biofluids, enabling real-time detection of ovulation phases. Therefore, this technology can be integrated into assisted reproductive technologies and smart home appliances, such as intelligent toilets and smart electric toothbrushes for noninvasive, real-time, and dynamic ovulation monitoring.