Prediction of fertile window and menstruation day through machine learning based on women’s physiological parameters. Not Applicable
Conditions
Interventions
This is a prospective observational cohort study conducted at the Obstetrics and Gynecology Hospital of Fudan University in Shanghai, China. Participants were recruited from November 2021 to September
otherwise, the participants are considered to have irregular menstrual cycles. Participants will be followed up with at least two complete menstrual cycles. Women are required to wear the Huawei Band
Sponsors
Obstetrics and Gynecology Hospital of Fudan University
Eligibility
Sex/Gender
Female
Inclusion criteria
Inclusion criteria: 1. Age 18~45 years old 2. Non-pregnant women 3. Have a menstrual cycle 4. Subjects with regular menstrual cycle; the duration of cycle days must be between 21 and 35 days (including 21 and 35 days); the duration of the menstrual period must not exceed 7 days; the cycle must remain regular, and the difference in days between adjacent cycles must be less than 7 days 5. Subjects with irregular menstrual cycles: do not meet the conditions of regular subjects 6. Sign the informed consent form
Exclusion criteria
Exclusion criteria: 1. Suffering from major systemic diseases 2. Pregnancy history within six months 3. Breastfeeding 4. Currently taking or planning to take hormones and other medications that affect the menstrual cycle 5. Passing across time zones 6. Sleep disorders 7. Other reasons that make researchers believe the patient is not suitable to participate in this study
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| The sensitivity, specificity and accuracy of fertile-window prediction and menstruation prediction were measured using data collected from machine-learning algorithms based on the wrist skin temperature and heart rate after every participant completed the follow-up | — |
Secondary
| Measure | Time frame |
|---|---|
| The alteration pattern of wrist skin temperature, heart rate, heart rate variability, and respiratory rate during a menstrual cycle among regular and irregular menstruators will be measured with the Huawei Band 6 Pro at night sleep at least for five hours | — |
Countries
China
Contacts
Public ContactHefeng ;Yanting Huang;Wu
;
Outcome results
None listed