Women who are trying to get pregnant often find it difficult to determine their fertility windows. Tracking basal body temperature (BBT) is a common method of predicting ovulation. The traditional way to track cycles by taking the woman’s temperature when she first arises gives a single daily data point that can easily be thrown off by other factors. We have looked in the past at Prima-Temp’s Bloom internal sensor, the Ava wristband fertility tracker, and a study published in Nature based on heart rates to detect fertility.
Yono Labs has introduced YONO, a non-invasive in-ear device that collects hundreds of temperature data points throughout the night. YONO consists of a single, small, silicon-encased earbud designed to be worn all night, a small bedside base station, and a mobile app. No data is transmitted while the woman is sleeping, but upon awakening, the earpiece is placed in the base station. The data is then transmitted to an associated mobile device via Bluetooth. YONO’s AI app has machine learning algorithms that plot monthly fertility charts to predict ovulation. Users can enter other information and physical symptoms to learn about hormonal health during menstrual cycles. According to the company, YONO is useful for natural family planning, cycle tracking, and early pregnancy monitoring as well as predicting fertility windows. For example, if during the first weeks or months of pregnancy the woman’s BBT is low, she should see her doctor.
With standard BBT temperature measurement, women have to wake up at the same time each day and stay stationary in bed, all to get one data point. The advantages of YONO are that you can wake up anytime and immediately get up and start your day, plus have more than 100 data points. According to Yono Labs, ear temperature readings are the most accurate. As wearable health tech devices mature, accuracy, comfort, and minimal user action requirements will be increasingly important.