Ava Bracelet Can Detect Changes in Physiology and Predict Fertility: Study

Ava bracelet study


Ava bracelet study

A recent study published in the JMIR shows that Ava Bracelet, a bracelet that tracks ovulation, can detect women’s physiological changes and predict fertility. Lea von Bidder from Ava Science will be speaking at our WT | Wearable Technologies Conference in San Francisco, July 9-10.

Previous research exploring hormonal changes in the menstrual cycle have identified biological responses to individual hormone shifts. For example , clinical studies have shown that after the release of postovulation progesterone, women’s nightly basal body temperature rises from 0.28 to 0.56 ° C. In the past, however, only 1 or 2 of these physiological features were sampled in a given study, requiring participants to come to a laboratory or hospital clinic multiple times throughout their cycle.

Researchers agreed to investigate how a wearable bracelet can detect Wrist Skin Temperature (WST), heart rate, HRV, respiratory rate, and skin perfusion from wearers for the new research. Using AI and machine learning, the team sought to develop a real-time algorithm that could identify the fertile window.

The team recruited 237 Swiss women who searched out conceptions for their prospective longitudinal research. Both participants were given an Ava bracelet to wear at night when they were sleeping for up to one year or when they became pregnant. The devices were synchronized to their smartphone apps, and in the past 24 hours the women had to complete an electronic diary about their activities. Finally, the participants took a urinary luteinizing hormone test at several points in a given cycle to determine the close of the fertile window.

ava bracelet can predict fertility

The results showed that the Ava bracelet was able to detect significant phase-based shifts in WST, heart rate and respiratory rate at the same time.

Researchers said their findings had been robust to covariates at the regular, individual, and cycle stage. Their machine learning algorithm can also detect the fertile window with an accuracy of 90 per cent.

“Our contributions demonstrate the effect of the incorporation into health care through artificial intelligence and machine learning. By simultaneously tracking various physiological parameters, wearable technology improves uniquely on retrospective methods for understanding of fertility and enables the first real-time predictive ovulation model, “the researchers wrote.

The most creative wearables event will be back at SEMICON West on 9-10 July to celebrate the 34th edition of the WT Wearable Technologies Conference Series in beautiful San Francisco. Topics include data analytics in professional sports, wearable prevention, treatment and rehabilitation, the future of digital health, medication and adherence, smart patches, optimisation of workflow and, workflow optimization and workforce safety and much more – featuring international leaders and experts of the wearables industry´s biggest names including Abbott, Autodesk, Datwyler, Kopin, Maxim Integrated, Multek, NFLPA, Omron, SharkDreams, Qualcomm,and many more.

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