Effect of Different Phases of Menstrual Cycle on Heart Rate Variability (HRV)

Brar, Tejinder Kaur; Singh, Kapil; Kumar, Avnish

doi:10.7860/jcdr/2015/13795.6592

Cited by 64 publications

(64 citation statements)

References 7 publications

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“…Parasympathetic input to the heart dominates during the follicular phase, lowering resting heart rate and elevating HRV (RMSSD) (Sato et al, 1995). Sympathetic input to the heart dominates during the luteal phase, elevating heart rate and depressing HRV (RMSSD) (Sato et al, 1995;Brar et al, 2015). Consequently, HRV (RMSSD) varies ~ 10 ms from the follicular to the luteal phase (Brar et al, 2015), with a marked decrease 14 days before the end of the cycle (Visrutha et al, 2012).…”

Section: Discussionmentioning

confidence: 99%

“…Unfortunately, the most widely used form of contraception, female hormonal contraception, has short and long term risks for many users, including but not limited to increased breast cancer rate (Mørch et al, 2017;Marsden, 2017), luteal phase deficiency (Gnoth et al, 2002), dysmenorrhea (Delbarge et al, 2002;Gnoth et al, 2002), altered cognition (Pletzer & Kerschbaum, 2014;Bradshaw et al, 2020) and depressed mood (Skovlund et al, 2016(Skovlund et al, , 2018. These risks, combined with increasing recognition that physiological systems vary in a structured manner across the menstrual cycle (Brar et al, 2015;Smarr et al, 2016Smarr et al, , 2017Grant et al, 2018), provide the impetus to develop FAM approaches that employ high-temporalresolution, non-invasive measures of physiology.…”

Section: Introductionmentioning

confidence: 99%

“…In rodents, the power of core body temperature URs exhibits a trough on the day of ovulation (Smarr et al, 2016(Smarr et al, , 2017. The translational capability of this method is supported by the association of gross timescale changes in DBT, HR and HRV by menstrual phase (Buxton & Atkinson, 1948;Sato et al, 1995;Leicht et al, 2003;Yildirir et al, 2006;Shechter et al, 2011;Uckuyu et al, 2013;Kräuchi et al, 2014;Brar et al, 2015;Uchida et al, 2019;Zhang et al, 2020). However, it is unknown if patterns of rhythmic change from continuous measures leading up to the LH surge associate with human reproductive status.…”

Section: Introductionmentioning

confidence: 99%

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

Grant

Newman²,

Kriegsfeld

2020

Preprint

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The 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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Grant

Newman²,

Kriegsfeld

2020

Preprint

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“…All subjects were studied in the afternoon (between 14:00 and 16:00) in a temperature controlled (20–22°C), constantly lit, quiet laboratory. Female participants were only studied during the follicular phase of their menstrual cycle, so as to limit for menstrual period and hormonal confounds previously documented in studies of resting autonomic activity [Brar et al, ]. Subjects were reclined at 45° on a bed.…”

Section: Methodsmentioning

confidence: 99%

Morphology of subcortical brain nuclei is associated with autonomic function in healthy humans

Ruffle

Coen

Giampietro

et al. 2017

Human Brain Mapping

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The autonomic nervous system (ANS) is a brain body interface which serves to maintain homeostasis by influencing a plethora of physiological processes, including metabolism, cardiorespiratory regulation and nociception. Accumulating evidence suggests that ANS function is disturbed in numerous prevalent clinical disorders, including irritable bowel syndrome and fibromyalgia. While the brain is a central hub for regulating autonomic function, the association between resting autonomic activity and subcortical morphology has not been comprehensively studied and thus was our aim. In 27 healthy subjects [14 male and 13 female; mean age 30 years (range 22-53 years)], we quantified resting ANS function using validated indices of cardiac sympathetic index (CSI) and parasympathetic cardiac vagal tone (CVT). High resolution structural magnetic resonance imaging scans were acquired, and differences in subcortical nuclei shape, that is, 'deformation', contingent on resting ANS activity were investigated. CSI positively correlated with outward deformation of the brainstem, right nucleus accumbens, right amygdala and bilateral pallidum (all thresholded to corrected P < 0.05). In contrast, parasympathetic CVT negatively correlated with inward deformation of the right amygdala and pallidum (all thresholded to corrected P < 0.05). Left and right putamen volume positively correlated with Additional Supporting Information may be found in the online version of this article. CVT (r 5 0.62, P 5 0.0047 and r 5 0.59, P 5 0.008, respectively), as did the brainstem (r 5 0.46, P 5 0.049). These data provide novel evidence that resting autonomic state is associated with differences in the shape and volume of subcortical nuclei. Thus, subcortical morphological brain differences in various disorders may partly be attributable to perturbation in autonomic function. Further work is warranted to investigate these findings in clinical populations. Hum Brain Mapp 39:381-392, 2018.

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“…Female participants were not enrolled because HRV might be affected by the menstrual cycle [26]. Before the experiment, we asked the participants whether they were suffering from any ailments of diseases or were taking any medicines.…”

Section: Participantsmentioning

confidence: 99%

Predicting Changes in Cognitive Performance Using Heart Rate Variability

Tsunoda

Chibá

Yoshida

et al. 2017

IEICE Trans. Inf. & Syst.

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SUMMARY In this paper, we propose a low-invasive framework to predict changes in cognitive performance using only heart rate variability (HRV). Although a lot of studies have tried to estimate cognitive performance using multiple vital data or electroencephalogram data, these methods are invasive for users because they force users to attach a lot of sensor units or electrodes to their bodies. To address this problem, we proposed a method to estimate cognitive performance using only HRV, which can be measured with as few as two electrodes. However, this can't prevent loss of worker productivity because the workers' productivity had already decreased even if their current cognitive performance had been estimated as being at a low level. In this paper, we propose a framework to predict changes in cognitive performance in the near future. We obtained three principal contributions in this paper: (1) An experiment with 45 healthy male participants clarified that changes in cognitive performance caused by mental workload can be predicted using only HRV. (2) The proposed framework, which includes a support vector machine and principal component analysis, predicts changes in cognitive performance caused by mental workload with 84.4 % accuracy. (3) Significant differences were found in some HRV features for test participants, depending on whether or not their cognitive performance changes had been predicted accurately. These results lead us to conclude that the framework has the potential to help both workers and managerial personnel predict what their performances will be in the near future. This will make it possible to proactively suggest rest periods or changes in work duties to prevent losses in productivity caused by decreases of cognitive work performance.

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Effect of Different Phases of Menstrual Cycle on Heart Rate Variability (HRV)

Cited by 64 publications

References 7 publications

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

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

Morphology of subcortical brain nuclei is associated with autonomic function in healthy humans

Predicting Changes in Cognitive Performance Using Heart Rate Variability

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