Comparative Analysis of Heart Rate Variability During Different Phases of Menstrual Cycle in Eumenorrhea & Dysmenorrhea Subjects

Abstract A method for determination of the Hurst exponent based on Analysis of Variance for processing of medical data sequences is proposed in the paper. It is compared to the “rescaled adjusted range method” developed by Hurst and applied in this paper to heart rate variability data. The obtained results and the performed comparative analysis demonstrate the possibility for effective application of the proposed method in novel medical information systems.

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Effects of Menstrual Cycle on Cardiac Autonomic Innervation As Assessed By Heart Rate Variability

Annals of Noninvasive Electrocardiology ◽

10.1111/j.1542-474x.2001.tb00140.x ◽

2001 ◽

Vol 7 (1) ◽

pp. 60-63 ◽

Cited By ~ 78

Author(s):

Aylin Yildirir ◽

Giray Kabakci ◽

Ebru Akgul ◽

Lale Tokgozoglu ◽

Ali Oto

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Menstrual Cycle ◽

Autonomic Innervation ◽

Cardiac Autonomic Innervation

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Heart rate variability across the menstrual cycle in young women taking oral contraceptives

Psychophysiology ◽

10.1111/psyp.12510 ◽

2015 ◽

Vol 52 (11) ◽

pp. 1451-1455 ◽

Cited By ~ 12

Author(s):

André L. Teixeira ◽

Plínio S. Ramos ◽

Lauro C. Vianna ◽

Djalma R. Ricardo

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Menstrual Cycle ◽

Oral Contraceptives ◽

Young Women

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Ultradian Rhythms in Heart Rate Variability and Distal Body Temperature Anticipate the Luteinizing Hormone Surge Onset

10.1101/2020.07.15.205450 ◽

2020 ◽

Author(s):

Azure D. Grant ◽

Mark Newman ◽

Lance J. Kriegsfeld

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Menstrual Cycle ◽

Body Temperature ◽

Inflection Point ◽

Ultradian Rhythms ◽

Fertility Awareness ◽

Lh Surge ◽

Non Invasive ◽

Sleep Timing

AbstractThe human menstrual cycle is characterized by predictable patterns of physiological change across timescales, yet non-invasive anticipation of key events is not yet possible at individual resolution. Although patterns of reproductive hormones across the menstrual cycle have been well characterized, monitoring these measures repeatedly to anticipate the preovulatory luteinizing hormone (LH) surge is not practical for fertility awareness. In the present study, we explored whether non-invasive and high frequency measures of 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 across the menstrual cycle. Cycles were examined from both pre- (n=45 cycles) and perimenopausal (n=10 cycles) women using days of supra-surge threshold LH and dates of menstruation for all cycles. For a subset of cycles, urinary estradiol and progesterone metabolites were measured daily around the time of the LH surge. Wavelet analysis revealed a consistent inflection point of ultradian rhythm (2-5 h) power of DBT and HRV that enabled anticipation of the LH surge at least 2 days prior to its onset in 100% of individuals. In contrast, the power of ultradian rhythms in heart rate, circadian rhythms in body temperature, and metrics of sleep duration and sleep timing were not predictive of the LH surge. Together, the present findings reveal fluctuations in distal body temperature and heart rate variability that consistently anticipate the LH surge and may aid in fertility awareness.Key PointsUltradian (2-5 h) rhythm power of distal body temperature and heart rate variability (RMSSD) exhibits a stereotyped inflection point and peak in the days leading up to the LH surge in premenopausal women.Circadian rhythms of distal body temperature and single time-point/day metrics do not permit anticipation of the LH surge.Measurement of continuous metabolic and autonomic outputs, enabling assessment of ultradian rhythms, may be of value to the fertility awareness method.

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