From heart rate and skin temperature to cycle fluctuations and menopausal symptoms, wearable devices are giving researchers an unprecedented real-world view of women’s health and could help transform the way menstrual and hormonal changes are monitored and managed.
Research: Decoding menstrual health across the lifespan: A scoping review of digital health tools in research. Image credit: BAZA Production/Shutterstock.com
Recent reviews published in magazines npj women’s health We investigated how digital health tools, particularly wearable devices and smartphone apps, are advancing research on women’s health related to menstruation and have the potential to help women understand and improve their menstrual health through targeted interventions.
Hormones and the menstrual cycle
Up to 90% of women report symptoms related to menstruation. These include dysmenorrhea, bloating, and mood swings. Premenstrual syndrome (PMS) affects up to 40% of women. In up to 8%, they become dysfunctional; A condition known as premenstrual dysphoric disorder (PMDD).
Similarly, perimenopausal symptoms increase the risk of depression and reduce well-being. From a purely economic perspective, menstrual symptoms and perimenopausal symptoms are estimated to each cost nearly $8.6 billion annually in Japan and more than $26 billion in the United States.
Menstrual symptoms are associated with significant fluctuations in hormone levels throughout the menstrual cycle. Follicle-stimulating hormone (FSH) rises during the follicular phase, culminating in high estrogen levels and a surge in luteinizing hormone (LH) levels. Combined with a small FSH peak, this triggers ovulation.
After ovulation, the follicle becomes the corpus luteum, which secretes progesterone, and levels of both LH and FSH decrease, although estrogen remains high. Eventually, both estrogen and progesterone decrease, resulting in menstrual bleeding.
Due to decreased ovarian reserve, FSH levels increase during perimenopause, and estrogen levels become increasingly fluctuating until they eventually decline permanently. Hormonal contraception also affects your hormonal profile during your menstrual cycle. Perimenopause, on the other hand, is associated with distinct hormonal fluctuations associated with a decline in ovarian function.
Non-invasive tests such as urine LH measurements and basal body temperature (BBT) graphing are often preferred over invasive methods to confirm ovulation.
Hormones, physiology, symptoms
Previous studies have linked hormonal changes to physiological parameters and menstrual/perimenopausal symptoms. High progesterone levels are associated with increased core body temperature, heart rate, and respiratory rate. Estrogen can also influence autonomic regulation and temperature-related physiological responses throughout the cycle, while changes in heart rate can occur with temperature changes.
These findings were often based on small sample sizes and infrequent measurements. Digital health tools enable large-scale, continuous, and cost-effective data collection outside the laboratory about physiological, symptomatic, and behavioral changes during the menstrual cycle and menopause.
In this review, the authors sought to determine whether these tools provide new insights, compare their results with previous results, and assess their accuracy in women’s health research across multiple parameters. This review analyzed 40 studies involving cohorts ranging from small pilot groups to approximately 19 million participants.
new insight
Characteristics of the menstrual cycle
Digital health research generally confirmed and fine-tuned earlier findings about menstrual cycle variation across women’s lives.
length and bleeding
The average ovulatory cycle length is usually 28 to 30 days, but many women’s cycles fall outside the traditional “normal” cycle range. Thus, 8-13% had shorter or longer cycles than “normal” and almost 20% had significant cycle-to-cycle variation.
On average, menstrual bleeding lasts about 4 to 5 days. Digital tools suggest later, more variable ovulation dates. The length of the follicular phase averages approximately 15-17 days, rather than the 13-14 days commonly reported in early laboratory studies. However, this may be influenced by differences in research methods.
Overall, digital tools support the existing concept of a relatively fixed luteal phase with variable follicular phase/ovulation timing that controls menstrual cycle length.
Age, BMI, demographics
Consistent with existing research, digital tools showed higher periodic variability in adolescents and young women, and after age 30 or during perimenopause. After the age of 25, your menstrual cycle becomes shorter.
Both low and high BMI were associated with increased variability and longer cycles. A new large-scale data insight was the association between high frequency of anovulation and abnormal bleeding and abnormal BMI.
Most studies were conducted in the United States and Europe, and most of the participants were white. Limited digital tools are beginning to reveal racial and ethnic differences in menstrual characteristics. For example, Black participants showed a 33% higher prevalence of infrequent menstruation compared to non-Hispanic White participants. More diverse studies are needed to validate such findings.
Women with polycystic ovary syndrome (PCOS) and hypothyroidism had longer menstrual cycles than other women, especially when both were present.
Physiological changes tracked by wearables
Wearables have successfully reproduced many known patterns of hormonal physiology across the menstrual cycle and age-dependent fluctuations.
skin temperature
Studies have consistently found that body temperature is lower during the follicular phase and higher during the luteal phase. In contrast to previous studies that showed that the lowest basal body temperature occurs just before ovulation, wearable products show that the lowest basal body temperature often occurs earlier than expected, often 5 days or more before ovulation. This can be important when tracking ovulation for pregnancy or contraception.
resting heart rate
The digital tool showed a consistent increase in resting heart rate of about 2.7 to 3.9 beats per minute from the follicular phase to the luteal phase, peaking in the five days just before ovulation. Variability decreases with age.
breathing rate
Consistent with laboratory studies, respiratory rate initially decreased before reaching a maximum value during the premenstrual phase.
heart rate variability (HRV)
HRV is generally higher during the follicular phase and lower during the premenstrual phase. Reduced HRV was associated with symptoms such as PMS and PMDD.
hormonal contraception
The wearable revealed that those taking the combination oral contraceptive pill had flatter heart rate variability and, similar to resting heart rate, showed a reversal trend throughout the cycle. Progestin-only contraception produced a pattern that more closely resembled natural cycles.
Hormonal contraception had different effects on menstrual cycles and bleeding depending on the type of contraceptive. However, little was discovered about the effectiveness of other forms of hormonal contraception. Similarly, the effects of hormonal contraception on motor parameters and menstrual symptoms remain unclear.
menstruation and symptoms
High cycle fluctuations were associated with heavy bleeding and other negative menstrual symptoms. The authors suggest that once validated, wearable data could be useful for screening and monitoring conditions such as PMS and PMDD, taking into account the changes observed between regular and irregular cycles.
sleep and physical activity
Research on sleep and exercise remains limited, with only modest effects on sleep metrics reported.
Research gap in perimenopause
Many researchers have excluded women with irregular cycles from studies on perimenopause. Although available evidence suggests that cycle length increases and variability across the lifespan increases sharply, data specifically addressing perimenopausal physiology remain limited. One study found that participants who were menstruating or perimenopausal had higher skin temperatures and respiratory rates compared to non-menstruating groups. Premenopausal women were associated with greater protection against coronavirus infection (COVID-19) than seen in postmenopausal women taking hormone replacement therapy (HRT).
Wearable accuracy
This review evaluated devices such as the Oura Ring, WHOOP band, Fitbit, Apple Watch, and Garmin watch. Although available validation evidence suggests that the Oura Ring may provide fairly reliable skin temperature measurements for menstrual cycle research, direct comparisons with gold standard core body temperature measurements remain limited, and the authors found the Oura Ring to be sufficiently accurate for this purpose.
Existing evidence suggests that wearables provide fairly accurate measurements of heart rate and breathing rate for the study of menstrual cycles. Although HRV measurements are useful, variations may be underestimated. Detection of sleep stages and measurement of sleep duration remained relatively inaccurate.
conclusion
This review concludes that wearable data has the potential to advance the understanding of menstruation-related changes at a population scale, but such data needs to be mapped across populations of diverse ethnic and age groups. This may help identify perimenopausal changes and fluctuations in a woman’s physiology across the lifespan.
They also point out opportunities for future research. These include simultaneous measurements of hormones, physiological and behavioral parameters, and menstrual symptoms, a rare combination in existing studies. Such information could serve as an intervention tool as well as form guidelines for managing these symptoms and optimizing performance in women.
They highlight the need to choose the right wearable for the research question, use standardized methods, and ensure privacy concerns are addressed.
Digital health tools can facilitate the characterization of healthy menstrual cycle norms in a more diverse group of women, allowing them to understand healthy norms and identify when medical evaluation should be warranted. This understanding is an important first step in developing effective solutions, as well as empowering women to take control of their health.
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Reference magazines:
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Johnson, S.C., O’Day, J., Krauss, E., et al. (2026). Decoding menstrual health across the lifespan: A scoping review of digital health tools in research. npj women’s health. Toi: https://doi.org /10.1038/ s44294-026-00146-7. https://www.nature.com/articles/s44294-026-00146-7
