Abstracts

Rationale: The menstrual cycle is a natural, recurring process in the female reproductive system that occurs in several phases. It involves a series of hormonal and physiological changes that prepare the body for the possibility of pregnancy. Various factors can contribute to variations in the menstrual cycle. Common factors influencing the length and regularity of the menstrual cycle include medical conditions, medications, stress, and more. Hormonal changes during the menstrual cycle can also impact certain medical conditions. For example, individuals with Catamenial epilepsy may experience more seizures when progesterone levels decrease, which occurs before menstruation, during the luteal phase, and at ovulation, followed by a rapid change in estrogen. Hormonal fluctuations may affect seizure likelihood for some individuals. Knowing the current menstrual phase and adjusting medication dosages before times of increased seizure risk may be beneficial. Heart rate (HR), electrodermal activity (EDA), and temperature (TEMP) are influenced by the phases of the menstrual cycle. This study aimed to identify menstrual phases in data recorded from patients with epilepsy and to compare the effects of these phases on physiological patterns with those observed in healthy subjects


Methods: In this study, long-term physiological ambulatory data was collected from epilepsy patients enrolled in the “My Seizure Gauge” project. This data was obtained through simultaneous recordings via an implanted EEG device (Neuropace RNS). Seizures were annotated and confirmed by a board-certified epileptologist. Additionally, HR, EDA and TEMP bio-signals from a wrist-worn device were collected from 15 healthy subjects to investigate physiological changes during menstrual cycles, providing a basis for comparison. Machine learning and statistical techniques were employed to determine the ovulation phase in data collected from six female epilepsy patients. It is important to note that theses patients were not diagnosed with catamenial epilepsy.


Results: In this study, we confirmed that these signals, measured during sleep, exhibit a biphasic pattern across the menstrual cycle. Specifically, we observed increased HR and TEMP during the luteal phase. Long-term physiological ambulatory data collected from six female subjects with epilepsy revealed a similar pattern in two ovulating subjects with low seizure frequency. The remaining subjects were either non-ovulating or in their menopausal phase. The correlation between seizure occurrence and menstrual cycle phases is currently under investigation.


Conclusions: Investigating gender-specific parameters that affect seizure risk and incorporating these findings into epilepsy management for women can significantly improve their health-related quality of life. The preliminary findings of this study indicate that subjects with a low seizure burden exhibit HR, EDA, and TEMP patterns consistent with typical menstrual cycles. These insights could assist in forecasting seizure risk for individuals with catamenial epilepsy.


Funding: This study was supported by the National Science Foundation under grant CBET-2138378.