Wearable devices may help detect menstrual health changes earlier

By Dr. Liji Thomas, MDReviewed by Lauren HardakerMay 27 2026

From heart rate and skin temperature to cycle variability and menopause symptoms, wearable devices are giving researchers an unprecedented real-world view of women’s health - and could help transform how menstrual and hormonal changes are monitored and managed.

Study: Decoding menstrual health across the lifespan: a scoping review of digital health tools in research. Image credit: BAZA Production/Shutterstock.com

A recent review published in the journal npj Women’s Health examined how digital health tools, especially wearable devices and smartphone apps, are advancing research on menstrual-associated women’s health, and could help women understand and improve it through targeted interventions.

Hormones and the menstrual cycle

Up to 90 % of women report menstrual-associated symptoms. These include dysmenorrhea, bloating, and mood swings. Premenstrual syndrome (PMS) affects up to 40 % of women. In up to 8 %, these are disabling, a condition known as premenstrual dysphoric disorder (PMDD).

Similarly, perimenopausal symptoms increase the risk of depression and reduced well-being. In purely economic terms, menstrual and perimenopausal symptoms, respectively, are estimated to cost Japan nearly $8.6 billion and the US over $26 billion annually.

Menstrual symptoms are linked to marked fluctuations in hormone levels throughout the menstrual cycle. Follicle-stimulating hormone (FSH) rises during the follicular phase, culminating in high estrogen levels and a spike in luteinizing hormone (LH) levels. Coupled with a smaller FSH peak, this triggers ovulation.

Post-ovulation, the follicle becomes a progesterone-secreting corpus luteum, and both LH and FSH levels decline, though estrogen remains high. Finally, both estrogen and progesterone drop, resulting in menstrual bleeding.

Declining ovarian reserve leads to higher FSH levels during perimenopause, with increasingly variable estrogen levels before a final permanent drop. Hormonal contraception also affects the hormonal profile during the menstrual cycle. Perimenopause, meanwhile, is associated with distinct hormonal fluctuations linked to declining ovarian function.

Noninvasive tests such as urinary LH measurement and basal body temperature (BBT) charting are often preferred over invasive methods for confirming ovulation.

Hormones, physiology, and symptoms

Earlier research linked hormonal changes to physiological parameters and menstrual/perimenopausal symptoms. High progesterone levels are associated with increased core temperature, heart rate, and respiratory rate. Estrogen may also influence autonomic regulation and temperature-related physiological responses throughout the cycle, though some heart rate changes may occur secondary to temperature shifts.

These findings were often based on small sample sizes and infrequent measurements. The use of digital health tools offers out-of-lab, large-scale, continuous, cost-effective data collection on physiological, symptomatic, and behavioral changes during the menstrual cycle and menopause.

In this review, the authors sought to determine whether these tools provided new insights, compare the findings with earlier results, and evaluate their accuracy in women’s health research across multiple parameters. The review analyzed 40 studies involving cohorts ranging from small pilot groups to nearly 19 million participants.

New insights

Menstrual cycle characteristics

Digital health studies generally confirmed and fine-tuned earlier laboratory findings on menstrual cycle variability across a woman’s life.

Length and bleeding

Average ovulatory cycle length was typically 28–30 days, but many women had cycles outside the traditional “normal” cycle ranges. Thus, 8–13 % had shorter or longer cycles than ‘standard’, and nearly 20 % had significant cycle-to-cycle variability.

Menstrual bleeding lasted around 4–5 days on average. Digital tools suggest a later and more variable ovulation date, with follicular phase lengths averaging around 15-17 days rather than the 13-14 days commonly reported in earlier laboratory studies. This could be affected by the differences between study methods, however.

Overall, digital tools support the existing concept of a relatively fixed luteal phase, with a variable follicular phase/ovulation timing that drives menstrual cycle length.

Age, BMI, and demographics

In line with existing studies, digital tools showed higher cycle variability in adolescents and younger women, and after age 30 or in perimenopause. Cycles shortened after age 25.

Both low and high BMI were associated with increased variability and longer cycles. A new large-data insight was the association of higher anovulation and abnormal bleeding with abnormal BMI.

Most studies were conducted in the USA and Europe and included mostly White participants. Limited digital tools have begun to show some racial and ethnic differences in menstrual characteristics. For instance, Black participants showed a 33 % higher prevalence of infrequent menstruation compared with White non-Hispanic participants. More diverse studies are required to validate such findings.

Women with polycystic ovarian syndrome (PCOS) and hypothyroidism had longer cycles than others, especially when both were present.

Physiological changes tracked by wearables

Wearables successfully reproduced many known patterns of hormonal physiology across the menstrual cycle and age-dependent variability.

Skin temperature

Studies consistently found lower temperatures during the follicular phase and higher temperatures during the luteal phase. In contrast to conventional studies showing that the minimum basal body temperature occurs immediately before ovulation, wearables show that, in many cases, the lowest temperature occurs earlier than expected, often more than five days before ovulation. This could be important in tracking ovulation for conception or contraception.

Resting heart rate

Digital tools showed a consistent increase in resting heart rate of about 2.7–3.9 beats per minute from the follicular to the luteal phase, peaking during the five-day period just before and including ovulation. The variability decreases with age.

Respiratory rate

Respiratory rate first dropped before rising to a maximum in the premenstrual phase, in agreement with laboratory studies.

Heart rate variability (HRV)

HRV was generally higher in the follicular phase and lowest in the premenstrual phase. Lower HRV was associated with symptoms, including those of PMS or PMDD.

Hormonal contraception

Wearables revealed that combined oral contraceptive users had flatter HRV variability with an inverted trend over the cycle, similar to resting heart rate. Progestin-only contraception produced patterns more similar to natural cycles.

Hormonal contraception affected cycle length and bleeding differently depending on the type of contraceptive. However, few findings were available about the effects of other forms of hormonal contraception. Similarly, the effects of hormonal contraception on athletic parameters and on menstrual symptoms remain unclear.

Physiology and symptoms

High cycle variability was associated with heavier bleeding and other negative menstrual symptoms. The authors suggest that, if validated, wearable data could help screen for and monitor conditions such as PMS and PMDD, given the changes observed between regular and irregular cycles.

Sleep and physical activity

Research on sleep and exercise remains limited, with only slight effects on sleep metrics being reported.

Perimenopause research gaps

Many researchers excluded women with irregular cycles from studies on perimenopause. The available evidence suggests increasing cycle length and steeply rising variability over the lifespan, though data specifically addressing perimenopausal physiology remain limited. One study identified higher skin temperature and respiratory rate in menstruating or perimenopausal participants compared with non-menstruating groups. Premenopause was associated with greater protection against coronavirus disease 2019 (COVID-19) than seen in postmenopausal women on hormone replacement therapy (HRT).

Accuracy of wearables

The review assessed devices including the Oura Ring, WHOOP band, Fitbit, Apple Watch, and Garmin watches. Though available validation evidence suggests the Oura Ring may provide reasonably reliable skin-temperature measurements for menstrual-cycle research, direct comparisons with gold-standard core body temperature measurements remain limited, the authors found the Oura Ring sufficiently accurate for this purpose.

Existing evidence suggests that wearables provide reasonably accurate measurements of heart and respiratory rates for menstrual cycle research. HRV measurements were useful, but sometimes underestimated variability. Sleep stage detection and sleep duration measurement remained relatively inaccurate.

Conclusions

The review concluded that wearable data could advance understanding of menstrual-related changes at the population scale, but such data needs to be mapped across populations with diverse ethnicities and age groups. This could help identify perimenopausal changes as well as fluctuations in women’s physiology across the lifespan.

They also point out opportunities for future research. These include simultaneous measurement of hormones, physiological and behavioral parameters, and menstrual symptoms, a combination rare in existing studies. Such information could shape guidelines for managing these symptoms and optimizing women’s performance, as well as serve as intervention tools.

They emphasize the need to choose the right wearables aligned with the research question, use standardized methods, and ensure privacy concerns are addressed.

By facilitating characterization of healthy menstrual cycle norms across a more diverse group of women, digital health tools can enable understanding of healthy norms and identify when medical evaluation is warranted. Not only is this understanding a vital first step toward developing effective solutions, but it also empowers women to take ownership of their health.

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