--- title: Can heart rate patterns measured by wearable devices help diagnose premenstrual disorders? description: Women with premenstrual disorders showed different heart rate patterns across their cycle compared to women without them. This could help develop diagnostic t url: https://niyora.com/research/papers/wearable-measured-heart-rate-variability-and-premenstrual-disorder-symptoms-2026/ --- - [Niyora](https://niyora.com/) - [Research](https://niyora.com/research/) - [Library](https://niyora.com/research/library/) - Can heart rate patterns measured by wearable devices help diagnose premenstrual disorders? Cohort study, 2026 # Can heart rate patterns measured by wearable devices help diagnose premenstrual disorders? Women with premenstrual disorders showed different heart rate patterns across their cycle compared to women without them. This could help develop diagnostic tools, but the study only shows the patterns exist rather than proving they can reliably diagnose the condition. Moderate study design 193 women (68 with confirmed premenstrual disorders) from a premenstrual emotion research study ## What they did 193 women (68 with confirmed premenstrual disorders) wore a fitness tracker that measured heart rate variability daily over 1 to 2 menstrual cycles. Researchers tracked daily symptoms using standardised questionnaires. ## What they found In both groups, heart rate variability metrics (SDNN, rMSSD, HF) decreased before the period and increased afterward, but the increase was more pronounced in women without premenstrual disorders. In women with premenstrual disorders, lower heart rate variability was linked to worse symptoms during the week before and after the period. ## What it means for you Heart rate variability changes with the menstrual cycle, and these changes may help spot premenstrual disorders. However, this is an observational study so we cannot say whether the heart rate changes cause the symptoms or simply happen alongside them. 193 women in study 68 with confirmed premenstrual disorders 293 menstrual cycles tracked ## About the study Original title Wearable-measured heart rate variability and premenstrual disorder symptoms across menstrual cycle Authors Pan Q, Zhou J, Chen M et al. Journal Archives of women's mental health Year 2026 Study design Cohort study Participants 193 What was tested Wearable fitness tracker measuring heart rate variability (monitoring device, not a treatment) Open access Yes Read the paper [doi.org/10.1007/s00737-026-01740-z](https://doi.org/10.1007/s00737-026-01740-z) Original abstract Background: Screening premenstrual disorders (PMDs) is time-consuming and challenging, resulting in delays in detection and treatment. To characterize the temporal dynamics of portable digital-marker across the menstrual cycle and its biological basis in PMDs, we investigated the menstrual fluctuation of wearable device-based real-time heart rate variability (HRV) through menstrual cycles and its associations with premenstrual disorders (PMDs) symptoms. Methods: A prospective study of female participants nested from the Care of Premenstrual Emotion Cohort was conducted. Daily HRV metrics were collected by the Huawei Fitness Tracker over 1-2 menstrual cycles. PMDs symptoms were assessed with the Daily Record of Severity of Problems on a daily basis. HRV variability across cycles was described using descriptive statistics and splines, while associations between HRV metrics and PMDs symptoms were estimated using a mixed-effect model. Results: In total, 193 participants (with 68 prospectively confirmed PMDs) were included, with measures from 293 menstrual cycles. In both women with and without PMDs, SDNN, rMSSD, and HF decreased before menses and increased afterwards; the increase trends were more pronounced in women without PMDs. During the week before or after menses, levels of these HRV metrics were inversely associated with PMDs symptoms among women with PMDs (e.g., rMSSD, postmenstrual week, β = -0·036 per SD, 95% CI: -0·065 to -0·048), whereas null association was noted for those without PMDs (β = -0·001, 95% CI -0·011 to 0·009; P-for-difference < 0·001). Conclusions: Wearable device-estimated HRV fluctuate across menstrual cycles, with varying strengths of association with PMDs symptoms between individuals with and without PMDs, which may facilitate the development of digital biomarkers for future PMDs diagnostics. Reproduced under CC-BY. ## Topics [Premenstrual syndrome (PMS)](https://niyora.com/research/topics/condition-pms/)[Premenstrual dysphoric disorder (PMDD)](https://niyora.com/research/topics/condition-pmdd/)[Apps and digital interventions](https://niyora.com/research/topics/treatment-digital-health/) Research tells you what helps on average. Niyora helps on the day it hits. Calm down, see it another way, and decide what to say, with a PMS and PMDD app built by a doctor. ## Related studies Randomised trial, 2019 Does online cognitive behavioral therapy help women with PMDD? Systematic review, 2026 Do digital tools and apps help reduce PMS and PMDD symptoms? Cohort study, 2026 Does the menstrual cycle phase affect how much physical activity women do? Cohort study, 2026 What life and psychological factors are linked to PMS and PMDD? Survey study, 2025 Does PMDD affect screen time, sleep quality, and how fast people react? Survey study, 2024 What features do people want in apps for menstrual mental health, and what drives app use? Ask AI about this page Copy prompt ChatGPT ↗ Claude ↗ Perplexity ↗ Google AI Mode ↗ Grok ↗