Digital women's health based on wearables and big data – new findings in physiological changes throughout the menstrual cycle
Introduction: Currently available options for family planning are often cumbersome and imprecise. Moreover, women's demand for insights into their cycles has increased due to older age at pregnancy and the need for better planning of life and career. The goal of the presented research project w...
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| Published in: | Geburtshilfe und Frauenheilkunde |
|---|---|
| Main Authors: | , , , , , , , |
| Format: | Conference Proceeding |
| Language: | English German |
| Published: |
13.10.2016
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| ISSN: | 0016-5751, 1438-8804 |
| Online Access: | Get full text |
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| Abstract | Introduction:
Currently available options for family planning are often cumbersome and imprecise. Moreover, women's demand for insights into their cycles has increased due to older age at pregnancy and the need for better planning of life and career. The goal of the presented research project was to find out if physiological data measured at the wrist allows for natural family planning.
Materials:
In a collaboration of scientists from the field of gynecology, physiology, sensor technology, and data science, a new solution for family planning was developed. It consists of a wrist worn sensor bracelet and intelligent algorithms. The bracelet contains various sensors which measure cardiovascular, movement, thermal, skin, and sleep parameters.
Methods:
The sensor bracelet was tested in a clinical study conducted by University Hospital Zurich and referenced with hormonal measurements. Daily surveys were filled out by the subjects to document confounding parameters. 85 menstrual cycles from 24 subjects were collected.
Results:
In a first step, temperature and pulse rate readings were analyzed. Both show differences between follicular and luteal phase. Minimum average resting pulse rate occurs in the follicular phase with 55.5 beats per minute and maximum in the luteal phase with 59.3 beats per minute. Wrist skin temperature follows the same pattern with 34.3 respectively 34.7 degrees Celsius. These phase-associated differences are currently used within an algorithm predicting ovulation. Further parameters will be used to improve prediction quality.
Conclusion:
The findings show that wrist-based measurements allow for measuring parameters which correlate with the changes throughout the menstrual cycle. |
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| AbstractList | Introduction:
Currently available options for family planning are often cumbersome and imprecise. Moreover, women's demand for insights into their cycles has increased due to older age at pregnancy and the need for better planning of life and career. The goal of the presented research project was to find out if physiological data measured at the wrist allows for natural family planning.
Materials:
In a collaboration of scientists from the field of gynecology, physiology, sensor technology, and data science, a new solution for family planning was developed. It consists of a wrist worn sensor bracelet and intelligent algorithms. The bracelet contains various sensors which measure cardiovascular, movement, thermal, skin, and sleep parameters.
Methods:
The sensor bracelet was tested in a clinical study conducted by University Hospital Zurich and referenced with hormonal measurements. Daily surveys were filled out by the subjects to document confounding parameters. 85 menstrual cycles from 24 subjects were collected.
Results:
In a first step, temperature and pulse rate readings were analyzed. Both show differences between follicular and luteal phase. Minimum average resting pulse rate occurs in the follicular phase with 55.5 beats per minute and maximum in the luteal phase with 59.3 beats per minute. Wrist skin temperature follows the same pattern with 34.3 respectively 34.7 degrees Celsius. These phase-associated differences are currently used within an algorithm predicting ovulation. Further parameters will be used to improve prediction quality.
Conclusion:
The findings show that wrist-based measurements allow for measuring parameters which correlate with the changes throughout the menstrual cycle. |
| Author | Kuebler, F Delgado Gonzalo, R Lemkaddem, A Stein, P Falco, L Annaheim, S Verjus, C Leeners, B |
| Author_xml | – sequence: 1 givenname: P surname: Stein fullname: Stein, P organization: Ava AG, Zurich, Schweiz – sequence: 2 givenname: L surname: Falco fullname: Falco, L organization: Ava AG, Zurich, Schweiz – sequence: 3 givenname: F surname: Kuebler fullname: Kuebler, F organization: Ava AG, Zurich, Schweiz – sequence: 4 givenname: S surname: Annaheim fullname: Annaheim, S organization: Empa – Swiss Federal Laboratories for Materials Science and Technology, St. Gallen, Schweiz – sequence: 5 givenname: C surname: Verjus fullname: Verjus, C organization: CSEM SA, Neuchâtel, Schweiz – sequence: 6 givenname: A surname: Lemkaddem fullname: Lemkaddem, A organization: CSEM SA, Neuchâtel, Schweiz – sequence: 7 givenname: R surname: Delgado Gonzalo fullname: Delgado Gonzalo, R organization: CSEM SA, Neuchâtel, Schweiz – sequence: 8 givenname: B surname: Leeners fullname: Leeners, B organization: Clinic for Reproductive Medicine, University Hospital Zurich, Zurich, Schweiz |
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| Snippet | Introduction:
Currently available options for family planning are often cumbersome and imprecise. Moreover, women's demand for insights into their cycles has... |
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| Title | Digital women's health based on wearables and big data – new findings in physiological changes throughout the menstrual cycle |
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