Bidirectional analysis of seizure patterns and menstrual cycle phases extracted from physiological signals

<i>Objective</i>. This exploratory study investigates cyclical changes in physiological features across the menstrual cycle in women with epilepsy, focusing on their potential relationship with seizure occurrence.<i>Approach</i>. Nocturnal data during sleep were collected from two women with ovulatory cycles and compared with data from healthy controls, two non-ovulatory women, one postmenopausal woman, and two male patients. The aim was to characterize signal patterns across different reproductive states and to explore whether menstrual-related rhythms correspond to seizure timing. Circular statistics mapped signals onto an angular scale, allowing identification of biphasic patterns linked to ovulation, while machine learning algorithms identified ovulatory phases.<i>Main Results</i>. In ovulatory participants, seizure activity predominantly occurred around the late luteal and early follicular phases (<i>p</i> < 0.05), and non-uniform and biphaisc trends were observed in temperature, resembling patterns in healthy participants. In contrast, individuals taking enzyme-inducing antiepileptic drugs showed disrupted physiological rhythms. Although hormonal fluctuations appear to drive cyclical patterns, additional rhythms (e.g. weekly) were also observed, suggesting multifactorial influences.<i>Significance</i>. These preliminary findings underscore the need to account for menstrual and other biological cycles in seizure forecasting models and provide a foundation for future studies involving larger cohorts.