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How The Ava Algorithm Predicts Your Fertile Window

How does Ava make predictions about your cycle and fertility window?

The short answer: A technique called machine learning combines knowledge of your cycle with the physiological data collected, and—voilà—the algorithm can make predictions about your cycle!

But, if you’re curious to know more about the science behind this process, this post will explain it in more detail and cover why Ava collects the data it does, what to expect during the first cycle you use it, how it identifies events in your cycle, and what information it filters out.

What does Ava do with the data collected every night?

With information that Ava has gathered about you in previously recorded cycles, along with information you provided about your cycles when you first started using the app, Ava calculates the probability that you are in a certain phase of your cycle. Ava then improves this prediction in real time by incorporating data from your physiological parameters. Based on these combined data science sources of information, Ava predicts your fertile window and ovulation.

Why does this work? The parameters that Ava measures correlate with the hormones estradiol and progesterone, which change throughout the menstrual cycle. In our clinical study, we learned to identify the fertile window of the cycle by looking at changes in physiological parameters.

The longer you use Ava, the accuracy of its predictions improve.

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What should I expect during my first cycle with Ava?

Once you receive your Ava bracelet, you can start using it on any day of your cycle.

The first time that you open the app, Ava already gives you a prediction of your fertile window based on the data that you entered during the onboarding process. This initial prediction resembles the classic calendar method and is based on a combination of scientific literature and findings from our clinical study.

If you start using Ava early in your first cycle, the algorithm will use the data from your physiological parameters to try to detect the beginning of your fertile window and the day of ovulation. However, if you start using Ava after the predicted day of ovulation, there will be no changes to your predictions for this cycle.

How does Ava identify my unique fertility window?

To identify the beginning of your fertile window, Ava relies on both changes in your physiological data, and prior knowledge about you (i.e. cycle length and physiological data of previously recorded cycles). Once the beginning of the fertile window is determined, Ava assumes that it will last for six days.

How does Ava identify ovulation?

Ovulation, which marks the end of the fertile window, is estimated using a combination of changes in your physiological data and prior knowledge from your previously recorded cycles.

Once ovulation has been recognized in your parameters, Ava closes your fertile window. Since this action depends on your physiological data and happens in real time, you may end up having more or fewer fertile days displayed in the app than what was initially predicted.

Ava updates its predictions in real-time

At the end of each cycle, Ava re-evaluates its predictions from the perspective of the cycle as a whole. This secondary analysis enables Ava to fine-tune the precision of its predictions. From this process, Ava gets to know you better and applies what it has learned to your following cycles.

Since this step is very important for the accuracy of your future predictions, it is essential that you keep wearing your Ava bracelet throughout the whole cycle, including after ovulation.

What information does Ava not include to make its predictions?

  • If your cycle was outside of the supported range of 24 to 35 days, the information from that cycle is not used to update Ava’s knowledge about you.
  • If you are sick or you have been drinking more alcohol than usual, this can be seen in your physiological signals. Ava filters out some of these effects but depending on when this occurs in your cycle it might influence the detection of the beginning or end of the fertile window.

Aarthi Gobinath, PhD

Aarthi Gobinath earned her PhD in neuroscience from the University of British Columbia. Her research covers the ways that stress affects the male and female brain differently.

She tackled the issue of sex bias in research by looking at why standard treatments for depression don't always work in the case of postpartum depression. Her work has been covered by Vice and Massive Science.

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