The menstrual cycle is characterized by predictable patterns of physiological change across timescales. Although patterns of reproductive hormones across the menstrual cycle, particularly ultradian rhythms, are well described, monitoring these measures repeatedly to predict the preovulatory luteinizing hormone (LH) surge is not practical. In the present study, we explored whether non-invasive measures coupled to the reproductive system: high frequency distal body temperature (DBT), sleeping heart rate (HR), sleeping heart rate variability (HRV), and sleep timing, could be used to anticipate the preovulatory LH surge in women. To test this possibility, we used signal processing to examine these measures in 45 premenopausal and 10 perimenopausal cycles alongside dates of supra-surge threshold LH and menstruation. Additionally, urinary estradiol and progesterone metabolites were measured daily surrounding the LH surge in 20 cycles. Wavelet analysis revealed a consistent pattern of DBT and HRV ultradian rhythm (2–5 h) power that uniquely enabled anticipation of the LH surge at least 2 days prior to its onset in 100% of individuals. Together, the present findings reveal fluctuations in distal body temperature and heart rate variability that consistently anticipate the LH surge, suggesting that automated ultradian rhythm monitoring may provide a novel and convenient method for non-invasive fertility assessment.

月经周期的特点是跨时间尺度的可预测的生理变化模式。尽管整个月经周期的生殖激素模式，特别是超日节律，已得到很好的描述，但反复监测这些措施来预测排卵前黄体生成素 (LH) 激增是不切实际的。在本研究中，我们探讨了是否可以使用与生殖系统相关的非侵入性措施：高频远端体温（DBT）、睡眠心率（HR）、睡眠心率变异性（HRV）和睡眠时间来预测女性排卵前 LH 激增。为了测试这种可能性，我们使用信号处理来检查 45 个绝经前和 10 个围绝经期周期中的这些测量值以及超峰值 LH 和月经的日期。此外，在 20 个周期内，每天测量 LH 峰值周围的尿雌二醇和孕酮代谢物。小波分析揭示了 DBT 和 HRV 超电节律（2-5 小时）功率的一致模式，这使得 100% 的个体能够在 LH 激增前至少 2 天进行预测。总之，目前的研究结果揭示了远端体温和心率变异性的波动，这些波动始终预示着 LH 激增，这表明自动亚电节律监测可能为非侵入性生育力评估提供一种新颖且方便的方法。