ClinicalTrials.gg
Active, not recruitingNCT07248046SMOMUpdated Jul 27, 2026

Smartphone vs Manual Interpretation of Biomarkers for Ovulation and Luteal Phase Detection (SMOM Study)

An observational study in Fertility, Mobile Applications and Artifical Intelligence, sponsored by Bruyère Health Research Institute.. Active, not recruiting at 1 site in Canada. Open to female participants aged 16 Years to 45 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-07-27.

Sponsored by Bruyère Health Research Institute. · Observational

Study type
Observational
Model
Other
Time perspective
Prospective
Enrollment
30
Ages
16 Years to 45 Years
Sex
Female
01

Study summary

This study will compare different combinations of fertility signs (cervical mucus (CM), luteinizing hormone [LH], pregnanediol glucuronide [PDG], and basal body temperature [BBT]) to determine which are most reliable for identifying ovulation and luteal phase length. Thirty existing Premom App users will track daily observations for three menstrual cycles. Participants will record mucus, perform urine tests, upload test strip photos to the Premom App, and measure BBT. Both participant readings and AI-assisted app readings will be analyzed. The main goal is to find which marker pairings give the most accurate picture of ovulation timing and luteal phase length. Secondary goals include understanding ease of use, the number of tests required, and whether the app improves accuracy.

Read the detailed description

This study examines how well different combinations of fertility signs-cervical mucus changes, hormone levels in urine, and body temperature-can help identify ovulation and luteal phase length. The study uses the Premom App, which allows users to record fertility signs and take photos of urine hormone test strips for AI-assisted interpretation. Four marker pairs will be compared: Mucus plus PDG, LH plus PDG, Mucus plus BBT, and LH plus BBT. Each participant will track three cycles, with both app-based and user-based readings analyzed. The study will assess which marker pairings are most accurate and user-friendly. Secondary endpoints include usability, test burden, and app vs. participant agreement. Results may support improvements in fertility awareness and digital health tools. Risks are minimal and involve time commitment for daily tracking. **This is an observational study. Participants are not assigned to any intervention; all fertility signs collected are part of their existing self-tracking using the Premom App. The study analyzes these naturally occurring data to compare marker pairings for identifying ovulation and luteal phase length.**

02

Conditions studied

  • Fertility
  • Mobile Applications
  • Artifical Intelligence
  • Cervical Mucus
  • Body Temperature
  • Luteinizing Hormone (LH)
  • Ovulation
  • Menstrual Cycle
  • Progesterone

Keywords

  • Ovulation
  • Luteal Phase
  • Menstrual Cycle
  • Fertility
  • Cervical Mucus
  • Luteinizing Hormone
  • Pregnanediol Glucuronide
  • Progesterone
  • Basal Body Temperature
  • Female Reproductive Physiology
  • Fertility Awareness-Based Methods
  • Mobile Applications
  • Smartphone App
  • Artificial Intelligence
  • Self-Testing
  • Home Diagnostic Tests
  • Observational Study
  • Prospective Studies
  • Digital Health
  • Women's Health
03

In context

Lead sponsor

Bruyère Health Research Institute. is the lead sponsor of 9 studies on the registry; 6 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
16 Years to 45 Years
Sexes eligible
Female
Accepts healthy volunteers
Yes
Sampling method
Non-probability sample

Study population

This study will include up to 30 adult women aged 16 to 45 years who have natural menstrual cycles and are current users of the Premom smartphone application for fertility tracking. All participants will reside within approximately 50 kilometers of Ottawa, Ontario, Canada. Participants must be off hormonal contraception for at least three months and willing to record daily fertility signs-cervical mucus, urinary LH and PDG test results, and basal body temperature-over three consecutive menstrual cycles. The study population represents healthy women of reproductive age who are already engaged in self-tracking of fertility and menstrual health using mobile technology.

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Female, aged 16 to 45
  • Natural menstrual cycles equal or less than 35 days
  • Off hormonal for more than 3 months
  • Current user of the Premom App
  • Willing to track cervical mucus, LH, PDG, and BBT for 3 full cycles
  • Lives within 50 km of study site in the Ottawa region
  • Able to provide

Exclusion criteria

Exclusion Criteria:

  • Pregnant or breastfeeding
  • Current hormonal therapy or
  • Known anovulatory disorders, e.g., Polycystic Ovary Syndrome, hypothalamic amenorrhea.
  • Very irregular or absent cycles
  • Not using the Premom App
  • Unable or unwilling to complete tracking or provide consent
Terms in these criteria, in plain language(2)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Contraception

Ways of preventing pregnancy. “Highly effective” methods fail less than 1% of the time a year when used correctly — for example an IUD or an implant.

Criteria usually say which methods count and how long to keep using them after the last dose, sometimes for male participants too. Some studies accept a partner’s vasectomy if it was confirmed successful and that person is the participant’s only sexual partner.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

05

Study design

Observational model
Other
Time perspective
Prospective
Enrollment
30 participants (estimated)
Patient registry
No

Groups and cohorts

  • Premom App Users

    Women aged 16 to 45 already using the Premom App, who will track daily fertility signs over 3 menstrual cycles.

    Other: Premom App-Assisted Fertility Tracking

Interventions

  • OtherPremom App-Assisted Fertility Tracking

    Participants use the Premom smartphone application (Easy Healthcare Corporation) to log daily fertility indicators - cervical mucus (CM), urinary luteinizing hormone (LH) strips, urinary pregnanediol glucuronide (PDG) strips, and basal body temperature (BBT) - over three menstrual cycles. Both participant-read and AI-interpreted app readings are compared to identify ovulation and luteal phase length. \*\*This is an observational study. Participants are not assigned to any intervention; all fertility signs collected are part of their existing self-tracking using the Premom App. The study analyzes these naturally occurring data to compare marker pairings for identifying ovulation and luteal phase length.\*\*

06

What researchers measure

Primary outcomes

  1. Agreement Between Marker Combinations and the Estimated Day of Ovulation (EDO)

    This outcome evaluates how four fertility marker combinations identify the Estimated Day of Ovulation (EDO) across three menstrual cycles. Participants will record daily cervical mucus (CM) observations, urinary luteinizing hormone (LH) and pregnanediol glucuronide (PDG) results, and basal body temperature (BBT), using both manual readings and the Premom smartphone app. For each cycle, the EDO will be established using validated physiologic indicators, including peak-type cervical mucus, the LH surge, the rise in PDG, and the post-ovulatory BBT shift. The EDO identified by each marker combination-cervical mucus plus PDG, LH plus PDG, cervical mucus plus BBT, and LH plus BBT. Agreement will be assessed by calculating the absolute day-difference between estimates.

    Time frame: Through completion of each menstrual cycle (cycle length up to 35 days), over 3 consecutive cycles per participant

  2. Luteal Phase Length Determined by Different Fertility Marker Combinations

    Number of days from the estimated day of ovulation to the onset of the next menstrual period, calculated for each marker combination and compared within subjects across three menstrual cycles.

    Time frame: Daily tracking through completion of each menstrual cycle (cycle length up to 35 days), over 3 consecutive cycles per participant.

Secondary outcomes

  1. User Satisfaction with Fertility Tracking Methods

    Participant satisfaction will be measured using the nineteen-item Participant Evaluation Survey, which examines clarity of instructions, ease of daily tracking, use of cervical mucus observations, LH and PDG tests, BBT measurements, app-based interpretation, time burden, and overall value. Each item uses a five-option Likert scale: Strongly Agree, Agree, Neutral, Disagree, and Strongly Disagree. Higher-rated responses indicate better usability, clearer instructions, lower perceived burden, and greater overall satisfaction.

    Time frame: At completion of Cycle 3 (cycle length up to 35 days).

  2. Agreement Between Participant and App Interpretations of LH and PDG Test Strips

    Concordance rate between participant visual interpretation and Premom App AI-assisted interpretation of LH and PDG test strip results, expressed as percent agreement.

    Time frame: At completion of Cycle 3 (cycle length up to 35 days).

  3. Testing Burden and Number of Testing Days per Cycle

    Average number of days participants perform LH and PDG testing per cycle across three cycles, recorded in the study tracking log and used to evaluate practicality of each marker combination.

    Time frame: Daily tracking Through completion of each menstrual cycle (cycle length up to 35 days), over 3 consecutive cycles per participant.

  4. App Usability and Functionality Evaluation

    Participant feedback on functionality, photo upload reliability, and AI test interpretation accuracy of the Premom App, rated through the end-of-study usability survey.

    Time frame: At completion of Cycle 3 (cycle length up to 35 days).

  5. Correlation Between Cervical Mucus-Defined and Standard Fertile Window

    Comparison between fertile days identified by cervical mucus observations and the classic Wilcox fertile window (the 5 days before and including ovulation), expressed as percent overlap and mean day difference.

    Time frame: Through completion of each menstrual cycle (cycle length up to 35 days), over 3 consecutive cycles per participant.

07

Study locations

1 site
  • St. Laurent Ideal Clinic
    Ottawa, Ontario K1G 3V4, Canada
08

References and documents

Publications

  • Youngster M, Luz A, Baum M, Hourvitz R, Reuvenny S, Maman E, Hourvitz A. Artificial intelligence in the service of intrauterine insemination and timed intercourse in spontaneous cycles. Fertil Steril. 2023 Nov;120(5):1004-1012. doi: 10.1016/j.fertnstert.2023.07.008. Epub 2023 Jul 23. PubMed 37490977 ↗
  • • Wang L, He L, Li J, Zeng D, Wen Y. T Line and C Line Detection and Ratio Reading of the Ovulation Test Strip Based on Deep Learning. In: Intelligent Data Engineering and Automated Learning - IDEAL 2021. Springer, Cham. Lecture Notes in Computer Science. 2021 Nov 23;(13113):625-636. https://www.researchgate.net/publication/356488630_T_Line_and_C_Line_Detection_and_Ratio_Reading_of_the_Ovulation_Test_Strip_Based_on_Deep_Learning
  • Potluri V, Kathiresan PS, Kandula H, Thirumalaraju P, Kanakasabapathy MK, Kota Sai Pavan S, Yarravarapu D, Soundararajan A, Baskar K, Gupta R, Gudipati N, C Petrozza J, Shafiee H. An inexpensive smartphone-based device for point-of-care ovulation testing. Lab Chip. 2018 Dec 18;19(1):59-67. doi: 10.1039/c8lc00792f. PubMed 30534677 ↗
  • Pattnaik S, Das D, Venkatesan VA. Validation of urinary reproductive hormone measurements using a novel smartphone connected reader. Sci Rep. 2023 Jun 7;13(1):9227. doi: 10.1038/s41598-023-36539-w. PubMed 37286704 ↗
  • Mendizabal-Ruiz G, Paredes O, Alvarez A, Acosta-Gomez F, Hernandez-Morales E, Gonzalez-Sandoval J, Mendez-Zavala C, Borrayo E, Chavez-Badiola A. Artificial Intelligence in Human Reproduction. Arch Med Res. 2024 Dec;55(8):103131. doi: 10.1016/j.arcmed.2024.103131. Epub 2024 Nov 29. PubMed 39615376 ↗
  • Leiva RA, Bouchard TP, Abdullah SH, Ecochard R. Urinary Luteinizing Hormone Tests: Which Concentration Threshold Best Predicts Ovulation? Front Public Health. 2017 Nov 28;5:320. doi: 10.3389/fpubh.2017.00320. eCollection 2017. PubMed 29234665 ↗
  • Leiva R, Ecochard R. Helping Patients to Predict and Confirm Ovulation with the Use of Combined Urinary Hormonal and Smartphone Technology: A Proof-of-Concept Retrospective Descriptive Case Series. Semin Reprod Med. 2024 Jun;42(2):90-99. doi: 10.1055/s-0044-1791702. Epub 2024 Oct 8. PubMed 39379045 ↗
  • Leiva R, McNamara-Kilian M, Niezgoda H, Ecochard R, Bouchard T. Pilot observational prospective cohort study on the use of a novel home-based urinary pregnanediol 3-glucuronide (PDG) test to confirm ovulation when used as adjunct to fertility awareness methods (FAMs) stage 1. BMJ Open. 2019 May 27;9(5):e028496. doi: 10.1136/bmjopen-2018-028496. PubMed 31133596 ↗
  • Gibbons T, Reavey J, Georgiou EX, Becker CM. Timed intercourse for couples trying to conceive. Cochrane Database Syst Rev. 2023 Sep 15;9(9):CD011345. doi: 10.1002/14651858.CD011345.pub3. PubMed 37709293 ↗
  • Ecochard R, Leiva R, Bouchard T, Boehringer H, Iwaz J, Plotton I. Descriptive analysis of the relationship between progesterone and basal body temperature across the menstrual cycle. Steroids. 2022 Feb;178:108964. doi: 10.1016/j.steroids.2022.108964. Epub 2022 Jan 20. PubMed 35065994 ↗
  • Ecochard R, Leiva R, Bouchard T, Boehringer H, Direito A, Mariani A, Fehring R. Use of urinary pregnanediol 3-glucuronide to confirm ovulation. Steroids. 2013 Oct;78(10):1035-40. doi: 10.1016/j.steroids.2013.06.006. Epub 2013 Jul 4. PubMed 23831784 ↗
  • Ecochard R, Duterque O, Leiva R, Bouchard T, Vigil P. Self-identification of the clinical fertile window and the ovulation period. Fertil Steril. 2015 May;103(5):1319-25.e3. doi: 10.1016/j.fertnstert.2015.01.031. Epub 2015 Feb 24. PubMed 25724738 ↗
  • Duane M, Stanford JB, Porucznik CA, Vigil P. Fertility Awareness-Based Methods for Women's Health and Family Planning. Front Med (Lausanne). 2022 May 24;9:858977. doi: 10.3389/fmed.2022.858977. eCollection 2022. PubMed 35685421 ↗
  • Bouchard TP, Fehring RJ, Schneider M. Pilot Evaluation of a New Urine Progesterone Test to Confirm Ovulation in Women Using a Fertility Monitor. Front Public Health. 2019 Jul 2;7:184. doi: 10.3389/fpubh.2019.00184. eCollection 2019. PubMed 31312631 ↗
  • Bouchard TP. Using Quantitative Hormonal Fertility Monitors to Evaluate the Luteal Phase: Proof of Concept Case Study. Medicina (Kaunas). 2023 Jan 10;59(1):140. doi: 10.3390/medicina59010140. PubMed 36676764 ↗

Individual participant data

Plan to share: Undecided

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jul 27, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT07248046
Lead sponsor
Bruyère Health Research Institute.
Responsible party
Sponsor
First posted
Nov 25, 2025
Start date
Jan 15, 2026
Primary completion
Sep 15, 2026 (estimated)
Completion
Dec 15, 2026 (estimated)
Last update
Jul 27, 2026

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is active, not recruiting, as verified in Jul 2026. You cannot join it, but the record below documents what was studied.

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