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Can Wrist-Worn Medical Devices Correctly Identify Ovulation?
Angela Niggli1,2, Martina Rothenbühler3, Maike Sachs1,2
1Department of Reproductive Endocrinology, University Hospital of Zürich, Frauenklinikstrasse 10, 8091 Zürich, Switzerland.
Sensors (Basel, Switzerland)
|December 23, 2023
Summary
Wearable sensors can accurately predict the fertile window by analyzing physiological changes during the menstrual cycle. This technology offers a convenient alternative to traditional ovulation predictor kits.
Area of Science:
- Reproductive endocrinology
- Biomedical engineering
- Wearable technology
Background:
- Hormonal shifts during the menstrual cycle influence physiological markers like body temperature and heart rate.
- Electronic wearables offer a potential non-invasive method for monitoring these changes.
- Predicting the fertile window is crucial for family planning and reproductive health.
Purpose of the Study:
- To evaluate the accuracy of a wrist-worn medical device in identifying the periovulatory period.
- To compare the efficacy of wearable sensor algorithms with traditional urinary ovulation tests.
- To validate the device's performance using both clinical study data and real-world user data.
Main Methods:
- A prospective observational study involved women aged 18-45 using a wrist-worn device and ovulation tests for at least three cycles.
- Generalized linear mixed-effects models were employed to analyze algorithm accuracy.
- Data from 61 participants (205 cycles) and 3268 real-world users (6081 cycles) were analyzed.
Main Results:
- The retrospective algorithm showed a mean error of 0.31 days in ovulation prediction.
- The retrospective and prospective algorithms correctly identified 75.4% and 73.8% of fertile days, respectively.
- Real-world data confirmed the accuracy of the retrospective algorithm developed in the clinical study.
Conclusions:
- Wearable sensors demonstrate significant potential for accurately detecting the periovulatory period.
- This technology provides a reliable and convenient alternative for fertile window prediction.
- Further integration of wearable sensors can advance reproductive health monitoring.
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