Ava’s research

Science drives our products, not the other way around. In developing services that support women across their reproductive lifetime, we hold ourselves to the most rigorous standards of scientific inquiry.

Scientific publications

Peer reviewed

Wearable sensors reveal menses-driven changes in physiology and enable prediction of the fertile window

Primary Research Question: What significant physiological changes can a wearable device detect across the menstrual cycle, and can we leverage machine learning to predict a woman’s fertile window in real time? Key Findings: Analyses from a clinical trial (n=237) revealed that the Ava bracelet can detect significant, concurrent phase-based shifts in wrist skin temperature, heart rate, and respiratory rate (all p<.001). These findings were robust to daily, individual, and cycle-level covariates. Furthermore, we developed a machine learning algorithm that can detect the 5-day fertile window with 90% accuracy (95% CI, 0.89 to 0.92).

Citation: Goodale BM, Shilaih M, Falco L, Dammeier F, Hamvas G, Leeners B. Wearable sensors reveal menses-driven changes in physiology and enable prediction of the fertile window: Observational study. J Med Internet Res. 2019;21(4):e13404. doi:10.2196/13404.

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Modern fertility awareness methods: Wrist wearables capture the changes of temperature associated with the menstrual cycle

Primary Research Question: Can wearable sensors accurately detect the biphasic shift in core body temperature that occurs during the menstrual cycle? Specifically, how does wrist skin temperature (WST) correlate with urinary tests of ovulation? Key Findings: Eumenorrheic women (n=136) wore the Ava bracelet while sleeping and took urinary LH tests to confirm ovulation. A sustained 3-day temperature shift was observed in 357/437 cycles (82%), with most temporal shifts (307/357, 86%) occurring on ovulation day or later. Phase-based changes in WST were impervious to lifestyle factors that previously have been shown to obfuscate basal body temperature readings.

Citation: Shilaih M, Goodale BM, Falco L, Kübler F, De Clerck V, Leeners B. Modern fertility awareness methods: Wrist wearables capture the changes of temperature associated with the menstrual cycle. Biosci Rep. 2018;38(6):BSR20171279. doi:10.1042/BSR20171279.

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Pulse rate measurement during sleep using wearable sensors, and its correlation with the menstrual cycle phases

Primary Research Question: This study investigated how a woman’s pulse rate changes across the menstrual cycle and correlates with the fertile window, as measured at home during sleep using the Ava bracelet. Key Findings: Two hundred seventy-four ovulatory cycles were recorded from 91 participants, with a mean cycle length of 27.3 days (±2.7). Pulse rate (PR) significantly increased during the fertile window compared to menses (2.1 beat-per-minute, p< 0.01). Moreover, PR during the mid-luteal phase was also significantly elevated compared to the fertile window (1.8 beat-per-minute, p< 0.01) and menses (3.8 beat-per-minute, p< 0.01).

Citation: Shilaih M, De Clerck V, Falco L, Kübler F, Leeners B. Pulse rate measurement during sleep using wearable sensors, and its correlation with the menstrual cycle phases, a prospective observational study. Sci Rep. 2017;7(1):1294. doi:10.1038/s41598-017-01433-9.

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Select medical congress & conference presentations

Oral Presentations

Monitoring changes in sleep patterns across the menstrual cycle using wearable sensors

Primary Research Question: This study evaluates the use of wearable devices, with reference to clinical measurements, in assessing the association of sleep patterns and quality with menstrual cycle phases. Key Findings: We recorded 541 cycles from 181 women. Total sleep time did not change across the menstrual cycle. However, deep sleep lasted significantly longer in the follicular and early luteal phases, and was shorter around menstruation. Women also woke up more often during the luteal phase. We consider the effect of potential covariates in our analyses (e.g., alcohol or caffeine intake).

Citation: Shilaih M, Falco L, Kübler F, Hamvas G, Cronin M, Leeners B. Monitoring sleep patterns change across the menstrual cycle using wearable sensors. Paper presented at: International Federation of Gynecology and Obstetrics 2018 World Congress; October 14-19, 2018; Rio de Janeiro, Brazil.

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Respiratory and cardiac monitoring at night using a wrist wearable optical system

Primary Research Question: Can a fully wearable system using photoplethysmography provide reliable estimations of heart rate and breathing rate during the night, compared to data from polysomnography (the gold standard of sleep studies)? Key Findings: For four nights, each participant (n=7) wore two Ava bracelets as well as a complete polysomnographic setup while sleeping to obtain reference signals. The resulting mean absolute errors for the wearable device compared to polysomnography data were less than one breath-per-minute for breathing rate, less than one beat-per- minute for heart rate, and around 17 ms for the beat-to-beat intervals.

Citation: Renevey P, Delgado-Gonzalo, Lemkaddem A, et al. Respiratory and cardiac monitoring at night using a wrist wearable optical system. In: 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE; 2018:2861-2864.

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Poster Presentations

Detecting the fertile window in irregular menstrual cycles using a wearable medical device

Primary Research Question: Can the Ava bracelet identify hormonal patterns and fertile window (FW) in women with irregular cycles, including subjects with and without diagnosed polycystic ovaries syndrome (PCOS)? Key Findings: Results included 161 cycles from women with irregular but undiagnosed/unknown PCOS (meanduration= 28.72 days [95% CI, 28.1-29.4]) and 61 cycles from women with confirmed PCOS (meanduration = 34.9 days [95% CI, 32.1-37.6]). Ava’s algorithm accurately identified fertile days in 82.1% of irregular cycles (95% CI, 80.0-83.8). Almost 30% of irregular cycles had more than one FW (mean=1.5 FW per cycle).

Citation: Rothenbühler M, Schmutz E, Hamvas G, et al. Detection of fertile window in irregular cycles using a wearable medical device. Poster presented at: International Federation of Fertility Societies 2019 World Congress; April 11-14, 2019; Shanghai, China.

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Previous cycle tracking with a wearable multiparameter device reduces time to conception

Primary Research Question: Do real-world Ava users who cycle track with a wearable device prior to trying to conceive become pregnant faster than women who did not cycle track first? Key Findings: Data from 12,540 women who purchased the Ava bracelet and reported a positive pregnancy test were included, with subjects divided between the prior cycle tracking (PCT; n=451) and no prior cycle tracking (NCT; n=12,089) groups. Time to pregnancy was significantly faster in the PCT group (mean=75 days, SD= 51 days) versus the NCT group (mean=89 days, SD=65 days; t(587)=-8.5936, p<.001).

Citation: Gibson S, Bilic A, Sakalidis V, Goodale BM, Shilaih M, Shulman L. Previous cycle tracking with a wearable multiparameter device reduces time to conception. Poster presented at: Central Association of Obstetricians and Gynecologists; Oct. 16-19, 2019; Cancun, Mexico.

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Detection of the fertile window using a wearable medical device and the calendar method: A comparative study

Primary Research Question: When identifying the six-day fertile window, how does artificial intelligence-based predictions from wearable sensor technology compare to the calendar method in accuracy and precision? Key Findings: The Ava bracelet’s accuracy in identifying the fertile days was 88.1% (SD=9.1%) compared to 76.8% (SD=5.1%) for the Standard Days method, 69.2% (SD=15.6%) for the Rhythm Method, and 67.6% (SD=16.1%) for the Alternative Rhythm Method. Furthermore, the wearable fertility tracker had the highest precision of any of the methods analyzed (70.3%, SD=21.9% v. 42.7%-47.7% for the calendar methods [SDs=7.6%-13.0%]).

Citation: Mouriki E, Bilic A, Goodale BM, et al. Detection of the fertile window using a wearable medical device and the traditional calendar method: A comparative study. Poster presented at: American Society of Reproductive Medicine Scientific Congress and Expo; Oct. 12-16, 2019; Philadelphia, PA, USA.

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Capturing the physiological characteristics of early pregnancy using wrist worn wearables

Primary Research Question: Can wearable sensors on the Ava bracelet capture physiological changes associated with early pregnancy, in particular differences in heart rate variability (HRV), pulse rate, breathing rate, and wrist-skin temperature? Key Findings: Analysis included 131 conceptive and 853 non-conceptive cycles from 330 women. In comparison to the late luteal phase of non-conceptive cycles, conceptive cycles were characterized by: an increase in pulse rate (1.43 beats/minute, p<.001), breathing rate (0.31 breaths/minute, p<.001), and wrist-skin temperature (0.05 C, p<.05). In addition, non-conceptive cycles were more likely to have lower HRV (-3.14 standard units, p<.001).

Citation: Shilaih M, Goodale BM, Falco L, Kübler F, Dammeier F, Leeners B. Capturing the physiological characteristics of early pregnancy using wrist worn wearables. Poster presented at: European Society of Human Reproduction and Embryology Annual Meeting; July 1-14, 2018; Barcelona, Spain.

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Proof of concept pilot study: Digital women’s health based on wearables and big data

Primary Research Question: The goal of this pilot study was to determine if physiological data measured via a wrist worn wearable sensor could allow for an individualized, AI-driven form of natural family planning. Key Findings: In a first step, wrist skin temperature (WST) and pulse rate readings were analyzed. Both showed significant differences between the follicular and luteal phase. The minimum average resting pulse rate occurred in the follicular phase (mean=55.5 beats/minute) and maximum resting pulse rate in the luteal phase (mean=59.3 beats/minute). WST followed the same pattern, with 34.3 compared to 34.7, respectively.

Citation: Stein P, Falco L, Kübler F, et al. Digital women’s health based on wearables and Big Data: New findings in physiological changes throughout the menstrual cycle. Poster presented at: Germany Society of Gynecology and Obstetrics (DGGG) Annual Meeting; Oct. 19-22, 2016; Stuttgart, Germany.

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Future research

Striving to make Ava a global leader in the field of women’s health, our scientists are pursuing projects related to:
  • Natural birth control / contraception
  • Irregular cycles & Polycystic ovary syndrome (PCOS)
  • Pregnancy complications
  • Menopause
  • Reproductive Endocrinology

Clinical and research collaboration

Ava is Interested in clinical and research cooperation in gynecology, obstetrics, and adjacent fields.

Please contact our Chief Medical Officer, Maureen Cronin, if you are interested in a research or clinical collaboration:

 

Contact

Maureen Cronin

Chief Medical Officer


Data security

Ava abides by the General Data Protection Regulation (GDPR), the highest security standard in both the European Union and the United States, and employs region-specific servers for data storage through Amazon Web Services (AWS). All user data is stored anonymously with the individual’s user ID, registration info, and other PII stored separately.

Find more information on the stringent security measures required by AWS and GDPR:

Additional information about Ava can be found here:

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