Nocturnal finger skin temperature in menstrual cycle tracking: ambulatory pilot study using a wearable Oura ring
Open accessAbstract
Background: Body temperature is a common method in menstrual cycle phase tracking because of its biphasic form. In ambulatory studies, different skin temperatures have proven to follow a similar pattern. The aim of this pilot study was to assess the applicability of nocturnal finger skin temperature based on a wearable Oura ring to monitor menstrual cycle and predict menstruations and ovulations in real life. Methods: Volunteer women ( n = 22) wore the Oura ring, measured ovulation through urine tests, and kept diaries on menstruations at an average of 114.7 days (SD 20.6), of which oral temperature was measured immediately after wake-up at an average of 1.9 cycles (SD 1.2). Skin and oral temperatures were compared by assessing daily values using repeated measures correlation and phase mean values and differences between phases using dependent t-test. Developed algorithms using skin temperature were tested to predict the start of menstruation and ovulation. The performance of algorithms was assessed with sensitivity and positive predictive values (true positive defined with different windows around the reported day). Results: Nocturnal skin temperatures and oral temperatures differed between follicular and luteal phases with higher temperatures in the luteal phase, with a difference of 0.30 °C (SD 0.12) for skin and 0.23 °C (SD 0.09) for oral temperature ( p < 0.001). Correlation between skin and oral temperatures was found using daily temperatures (r = 0.563, p < 0.001) and differences between phases (r = 0.589, p = 0.004). Menstruations were detected with a sensitivity of 71.9–86.5% in window lengths of ±2 to ±4 days. Ovulations were detected with the best-performing algorithm with a sensitivity of 83.3% in fertile window from − 3 to + 2 days around the verified ovulation. Positive predictive values had similar percentages to those of sensitivities. The mean offset for estimations were 0.4 days (SD 1.8) for menstruations and 0.6 days (SD 1.5) for ovulations with the best-performing algorithm. Conclusions: Nocturnal skin temperature based on wearable ring showed potential for menstrual cycle monitoring in real life conditions.
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The Oura algorithm sensitivity in detecting menses was 81.4% (window of ±3 days).
“- Sensitivity of the algorithm in detecting menses was 81.4% [window of ±3 days).”
From Temperature regulation in women: Effects of the menstrual cycle (2020) · cites this paper as [180]
The Oura algorithm sensitivity in detecting ovulation was 83.3% within a 6-day fertile window.
“- Sensitivity of the algorithm in detecting ovulation was 83.3% within a 6-day fertile window.”
From Temperature regulation in women: Effects of the menstrual cycle (2020) · cites this paper as [180]
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Cites
Bakdash, J. Z., & Marusich, L. R. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00456 · Cited by 2,067 · see citing works
Examining menstrual tracking to inform the design of personal informatics tools
Epstein, D. A., Lee, N. B., Kang, J. H., Agapie, E., Schroeder, J., Pina, L. R., Fogarty, J., Kientz, J. A., & Munson, S. (2017) · Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025635 · Cited by 346 · see citing works
Circadian rhythm of wrist temperature in normal-living subjects
Sarabia, J. A., Rol, M. A., Mendiola, P., & Madrid, J. A. (2008) · Physiology & Behavior · doi:10.1016/j.physbeh.2008.08.005 · Cited by 222 · see citing works
Direito, A., Bailly, S., Mariani, A., & Écochard, R. (2012) · Fertility and Sterility · doi:10.1016/j.fertnstert.2012.08.047 · Cited by 145 · see citing works
Gender-related Differences in Food Craving and Obesity.
Hallam, J., Boswell, R. G., DeVito, E. E., & Hedy Kober, A. (2016) · PubMed Central · Cited by 142 · see citing works
Goodale, B. M., Shilaih, M., Falco, L., Dammeier, F., Hamvas, G., & Leeners, B. (2019) · Journal of Medical Internet Research · doi:10.2196/13404 · Cited by 123 · see citing works
Circadian Variation of Sleep During the Follicular and Luteal Phases of the Menstrual Cycle
Shechter, A., Varin, F., & Boivin, D. B. (2010) · Sleep · doi:10.1093/sleep/33.5.647 · Cited by 119 · see citing works
Shilaih, M., Goodale, B. M., Falco, L., Kübler, F., De Clerck, V., & Leeners, B. (2018) · Bioscience Reports · doi:10.1042/bsr20171279 · Cited by 109 · see citing works
Fertility Awareness-Based Methods: Another Option for Family Planning
Pallone, S. R., & BERGUS, G. R. (2009) · The Journal of the American Board of Family Medicine · doi:10.3122/jabfm.2009.02.080038 · Cited by 105 · see citing works
Lei, T., Stannard, S. R., Perry, B. G., Schlader, Z. J., Cotter, J. D., & Mündel, T. (2017) · The Journal of Physiology · doi:10.1113/jp273176 · Cited by 101 · see citing works
Martínez-Nicolás, A., Meyer, M., Hunkler, S., Madrid, J. A., Rol, M. A., Meyer, A. H., Schötzau, A., Orgül, S., & Kräuchi, K. (2015) · Physiology & Behavior · doi:10.1016/j.physbeh.2015.06.014 · Cited by 93 · see citing works
Identification and prediction of the fertile window using NaturalCycles
Berglund Scherwitzl, E., Lindén Hirschberg, A., & Scherwitzl, R. (2015) · The European Journal of Contraception & Reproductive Health Care · doi:10.3109/13625187.2014.988210 · Cited by 90 · see citing works
DeVito, E. E., Herman, A. I., Waters, A. J., Valentine, G. W., & Sofuoglu, M. (2013) · Neuropsychopharmacology · doi:10.1038/npp.2013.339 · Cited by 88 · see citing works
Gradisar, M., & Lack, L. C. (2004) · Journal of Biological Rhythms · doi:10.1177/0748730403261560 · Cited by 82 · see citing works
Fertility awareness-based mobile application for contraception
Scherwitzl, E. B., Gemzell‐Danielsson, K., Sellberg, J. A., & Scherwitzl, R. (2016) · The European Journal of Contraception & Reproductive Health Care · doi:10.3109/13625187.2016.1154143 · Cited by 81 · see citing works
Is Oral Temperature an Accurate Measurement of Deep Body Temperature? A Systematic Review
Mazerolle, S. M., Ganio, M. S., Casa, D. J., Vingren, J. L., & Klau, J. F. (2011) · Journal of Athletic Training · doi:10.4085/1062-6050-46.5.566 · Cited by 80 · see citing works
Association between subjective and cortisol stress response depends on the menstrual cycle phase
Duchesne, A., & Pruessner, J. C. (2013) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2013.08.009 · Cited by 80 · see citing works
Uncovering Different Masking Factors on Wrist Skin Temperature Rhythm in Free-Living Subjects
Martínez-Nicolás, A., Ortiz‐Tudela, E., Rol, M. A., & Madrid, J. A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061142 · Cited by 67 · see citing works
Finger temperature after a finger-cooling test: influence of air temperature and smoking
Cleophas, T. J., Fennis, J. F. M., & Laar, A. V. (1982) · Journal of Applied Physiology · doi:10.1152/jappl.1982.52.5.1167 · Cited by 57 · see citing works
Freundl, G. (2003) · Human Reproduction · doi:10.1093/humrep/deg488 · Cited by 56 · see citing works
Luo, L., She, X., Cao, J., Zhang, Y., Li, Y., & Song, P. X. K. (2020) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2019.2916823 · Cited by 53 · see citing works
Roche, D. J. O., & King, A. (2014) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2014.10.013 · Cited by 49 · see citing works
Kräuchi, K., Konieczka, K., Roescheisen-Weich, C., Gompper, B., Hauenstein, D., Schoetzau, A., Fraenkl, S., & Flammer, J. (2014) · Chronobiology International · doi:10.3109/07420528.2013.829482 · Cited by 46 · see citing works
Matsuda-Nakamura, M., Yasuhara, S., & Nagashima, K. (2015) · The Journal of Physiological Sciences · doi:10.1007/s12576-015-0371-x · Cited by 45 · see citing works
Areas, R., Duarte, L. L., & Menna-Barreto, L. S. (2006) · Biological Rhythm Research · doi:10.1080/09291010600869752 · Cited by 29 · see citing works
Fukaya, K., Kawamori, A., Osada, Y., et al. (2017) · Statistics in Medicine · doi:10.1002/sim.7345 · Cited by 25 · see citing works
Chen, W., Kitazawa, M., & Togawa, T. (2009) · Annals of Biomedical Engineering · doi:10.1007/s10439-009-9746-6 · Cited by 15 · see citing works
Digital contraceptives based on basal body temperature measurements
Händel, P., & Wahlström, J. (2019) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.04.019 · Cited by 15 · see citing works
Demiańczyk, A., & Michaluk, K. (2016) · Ginekologia Polska · doi:10.5603/gp.2016.0090 · Cited by 8 · see citing works
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Research works printed but not linked: 1
- [26]Maijala A, Kinnunen H, Koskimäki H, Jämsä T and Kangas M. Comparison of menstrual phases with nocturnal temperature of the Oura ring and oral body temperature at wake-up. World Congress on Medical Physics and Biomedical Engineering; 2018; Prague, Czech Republic: IUPESM; 2018:312–313.
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Huhn, S., Axt, M., Gunga, H.-C., Maggioni, M. A., Munga, S., Obor, D., Sié, A., Boudo, V., Bunker, A., Sauerborn, R., et al. (2022) · JMIR mHealth and uHealth · doi:10.2196/34384 · Cited by 379 · see citing works
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Baker, F. C., Siboza, F., & Fuller, A. (2020) · Temperature · doi:10.1080/23328940.2020.1735927 · Cited by 262 · see citing works
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Smarr, B. L., Aschbacher, K., Fisher, S. M., Chowdhary, A., Dilchert, S., Puldon, K., Rao, A., Hecht, F. M., & Mason, A. E. (2020) · Scientific Reports · doi:10.1038/s41598-020-78355-6 · Cited by 133 · see citing works
- Authors
- Maijala, A., Kinnunen, H., Koskimäki, H., Jämsä, T., & Kangas, M.
- Affiliations
- University of Oulu (FI)
- Oulu University Hospital (FI)
- Corresponding author
- Maijala, Anna
- Venue
- BMC Women's Health
- Published
- 2019-11-29
- Volume
- 19
- Issue
- 1
- Pages
- 150-150
- ISSN
- 1472-6874 (ISSN-L)
- PMC
- PMC6883568
- OpenAlex
- W2990739358
- Cited by
- 107
- References
- 29
- Citations by year
- 2026: 25 · 2025: 19 · 2024: 20 · 2023: 13 · 2022: 20 · 2021: 7 · 2020: 3
- FWCI
- 7.15
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- BMC Women s Health (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Health Sciences › Medicine › Reproductive Medicine › Reproductive Health and Technologies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Menstrual Health and Disorders
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- menstrual cycle tracking, Oura Ring, wearable sensors, body temperature, oral temperature, ovulation prediction, follicular phase, luteal phase, fertility awareness, menstrual cycle monitoring
- MeSH terms
- Wearable Electronic Devices, Adult, Circadian Rhythm, Feasibility Studies, Female, Fertility, Humans, Menstrual Cycle, Ovarian Function Tests, Pilot Projects, Skin Temperature, Thermometry
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