The Fertility Tracker Method (or FTM) comes under the umbrella of fertility awareness-based methods.

FTM combines the logic of existing manual fertility awareness methods including the Calendar Method, the Calculothermal Method, and the Symptothermal Method in the automated process of the fertility tracker, using a self-learning algorithm to calculate the user’s fertile and infertile days. This process avoids the user error based misinterpretations that can occur with manual fertility awareness methods. (Pallon 2009; Barron 2005).

The first Fertility Tracker was developed by Dr. Hubertus Rechberg in 1986. His company, Valley Electronics, continues to develop and innovate Fertility Trackers worldwide, including the Pearly, Lady-Comp, Lady-Comp Baby and Daysy. 

The Fertility Tracker both tracks and documents the user’s basal body temperature, then makes an independent calculation of the fertile and infertile days using this data. The Fertility Tracker automatically stores the data and evaluates it using an intelligent, self-learning algorithm. Additionally, the algorithm continuously checks its own calculation results against its previously collected data, and thus learns to reliably distinguish between fertile and infertile days. 

All users have to do to practice FTM accurately is to regularly measure their basal body temperature and correctly input their menstruation days. The Fertility Tracker takes over all further steps and determines the fertility status of the user. 

The algorithm uses the menstrual start date as the beginning of a new cycle. Basal body temperature (BBT) is measured daily to establish the pre ovulation phase until the current temperature value has increased by a characteristic shift. Due to the lack of enough data in the first few cycles using the device, the algorithm assumes that all days (after 5 days of menstruation) up to ovulation could be fertile. That is the reason you will have more red (possible fertile) days in the first few cycles (figure 2 A). This mechanism is adjusted after continuous use of the device, in which infertile days during the pre-ovulation phase are calculated by learning from previously entered data and daily basal body temperature.

After this learning period when the Fertility Tracker gathers your personal data, the tracker will begin to pinpoint your ovulation and start your personal fertile window 5 days before your earliest likely predicted ovulation. This is calculated using the new data you have provided (basal body temperature, menstrual cycle start and end date, historical cycle data) and compared to statistical analysis of the database of menstrual cycle data. The algorithm ascertains the earliest day in your cycle you are likely to ovulate. The fertile phase will then continue until ovulation has been confirmed.

As soon as ovulation is calculated to have happened and the end of the fertile time is identified by a statistical temperature shift, the algorithm starts to assign post-ovulatory, infertile statuses to the following days. Each new day, statistical analyses are used to re evaluate whether you are still in the high-temperature luteal phase. The device waits until you enter menstruation, signaling a new cycle, or a prolonged high temperature phase that could indicate successful conception (figure 2 B).

The Temperature-Only Method is focused on the phase after ovulation. The, often much longer, pre-ovulation phase is considered to be potentially fertile. The method assumes infertile days after ovulation. With a relatively regular cycle, users can assume that about 20-30% of the days are infertile (including menstruation) with the Temperature-Only method. With the Fertility Tracker Method, the distribution of fertile and infertile days is about fifty-fifty for women with a regular cycle.

The Calendar Method calculation of the fertile window is based on the average length of the previous cycles. It is assumed that the post ovulation phase, the second half of the cycle after ovulation, is always 14 days long. The fertile window opens four days before and closes three days after the predicted time. Information from the current cycle (i.e. daily BBT measurement) is not taken into account in this type of calculation. Since ovulation, and thus the individual fertile window, can fluctuate by an average of 5 days within a year, this method is not accurate at all.

The classic Calculothermal Method, combines Basal Body Temperature with Ogino’s calendar calculation, which is the shortest cycle minus 18 to identify the start of the fertile time, with temperature to identify the end of the fertile time.

Based on the findings of the scientific work on natural family planning (NFP), Valley Electronics has developed a unique Method that allows a unique evaluation procedure through statistical and mathematical calculations. While the classical Calculothermal Method is based on a rigid construct, the Fertility Tracker Method makes use of the possibility to individually extend the infertile days after menstruation on the basis of already measured cycles. In a nutshell, the Calculothermal Method tries to predict the fertile window, while the Fertility Tracker Method (due to the lack of sufficient data) assumes that in the first few cycles all days after 5 days of menstruation could be fertile. 

These infertile days after menstruation are adjusted to the individual optimum with each cycle - the Fertility Tracker Method is actively learning. As soon as the ovulation is calculated to have happened, based on the measured BBT, the Fertility Tracker Method starts to assign mathematical post ovulatory, infertile status to the days. Each new day, this mathematical test is (re)evaluated to decide if you are still in the infertile luteal phase.

The trackers determine your fertile and infertile phase using an extensive database and proprietary algorithm. Based on five million menstrual cycles and an algorithm that draws on knowledge from more than 30 years of research, including several studies, they can give you reliable information about your menstrual cycle. The accuracy of this algorithm has been systematically tested. For the scientific study, 107,000 cycles (basal temperature, menstrual input) of 5,328 women from Germany and Switzerland were evaluated over a period of ten years.

The independently reviewed result shows that the trackers have an overall accuracy of 99.4% in differentiating infertile days versus fertile days. For more Information please click: 

Daysy Clinical Trial 2021

Fact Sheet Study282.1 KB / 06/21/2021

Just 0.6% of the days displayed were green, although they were in the fertile window and thus should have been "red" (possibly fertile) (see graph). However, 50% of these "false green days" were five days before ovulation and thus have only a minimal chance of pregnancy during this period.

The algorithm is created by combining two elements - the acquisition and learning of new data (your daily basal body temperature, start and end of menstruation, and accumulated past cycle data) and statistical analysis (e.g. the temperature rise that occurs after ovulation).

After a learning period, during which Daysy gathers your personal data, the algorithm begins to predict your ovulation and can open your fertile window (red days) at least five days before the earliest possible date of ovulation (figure 1 A above). Once a rise in basal body temperature is registered and the algorithm can confidently recognize ovulation, Daysy will show you subsequent individual infertile (green) days until the next menstruation (figure 1 B above).

In the background, the algorithm takes into account the previous average temperature for each measurement, so it is also possible to tolerate occasional outliers or measurement failures. If Daysy does not have sufficient data to deliver a red (possible fertile) or green (infertile) indicator, Daysy will display a yellow (learning/cycle fluctuation) indicator and remember the fluctuation for the coming cycle. In short, Daysy learns!

Lady-Comp & Daysy use a very sensitive sensor to measure the basal body temperature. The sensor’s most unique feature is that it waits for the mean temperature value, which can take up to 60 seconds.

The sensor warms up before it records your basal body temperature in order to receive an accurate result. The trackers wait until the final temperature value has stabilized to complete the reading. If the temperature drops during the measurement (for example, due to cold air that gets into the mouth through breathing), the sensor waits for it to rise again and stabilize. This unique feature differentiates Daysy & Lady-Comp from less sophisticated basal body thermometers. This method of temperature tracking ensures that the measurement is as precise as possible.

• Lady-Comp as an aid in natural family planning. [Freundl 1992]
• Monitoring of ovulation by sophisticated digital electronic BBT recording "Babycomp" in patients with unexplained infertility.  [Dessole 1997]
• The retrospective study of the reliability, acceptance and safety. [Bachhofer 1997]
• Retrospective clinical trial of the electronic fertility indicator LadyComp/BabyComp. [Freundl 1998]
• Kongress: Congresso della Societa Italiana della Contraccezione 16.-18. Juni 2005 Lettura Baby-Comp Dr. Hubertus Rechberg: Prevention und Babyplanung
• Review: Calculation of the Pearl Index of Lady-Comp, Baby-Comp and Pearly cycle computers used as a contraceptive method [Binkiewicz 2010]
• Survey: Evaluation of the effectiveness of selected natural fertility symptoms used for contraception: estimation of the Pearl index of Lady-Comp, Pearly and Daysy cycle computers based on 10 years of observation in the Polish market. [Demianczyk 2016]
• The Performance of a Fertility Tracking Device [Roemer 2021]