Evaluating the Accuracy of O’Tracker: A Stick-To-Skin Wireless BBT Sensor to Identify Fertility Window

Main Article Content

Girish Godbole
Gautam Morey
Navani Tawar
Ayesha Rathod

Abstract

Objective: The study identifies the event of ovulation using an IoT-based device called “O’Tracker” in contrast with the
transvaginal ultrasound in trying to conceive women.
Methods: This prospective study includes a total of 30 cycles from 27 women who were trying to conceive. They were asked to use the O’Tracker device from the 10th day of their menstrual cycle to the 18th day, i.e., 8 days for 7 hours per night.
Result: In the conclusive evaluation, a total of 30 cycles underwent scrutiny, wherein the O’Tracker predictions of the
ovulation window were aligned with physicians’ predicted ovulation window from the USG reports in 27 cycles, indicating
a commendable accuracy rate of 90%. Upon proximity to the ovulation window predicted by O’Tracker with those derived
from the USG report (considered as the ground truth for validation) the concordance was observed in 25 out of 27 accurately
predicted ovulatory cycles. Furthermore, when compared to the physician-predicted ovulation window from USG reports,
O’Tracker exhibited concordance in 23 out of 27 cycles.
Conclusion: The study evaluation reveals that O’Tracker attains a 90% accuracy in predicting ovulation as compared to
physician assessment, demonstrating a match rate exceeding 90% with fertile windows ascertained through ultrasound
monitoring. This level of precision stands on with established traditional diagnostics methodologies. O’Tracker manifests a
user-friendly and accessible digital ovulation monitoring platform.

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How to Cite
Godbole, G. ., Morey, G. ., Tawar, N. ., & Rathod, A. . (2024). Evaluating the Accuracy of O’Tracker: A Stick-To-Skin Wireless BBT Sensor to Identify Fertility Window. International Journal of Health Technology and Innovation, 3(01), 5–10. https://doi.org/10.60142/ijhti.v3i01.02
Section
Research Article

References

Beshay VE, Carr BR. Hypothalamic–Pituitary–Ovarian Axis and Control of the Menstrual Cycle. In: Falcone T, Hurd WW, editors. Clinical Reproductive Medicine and Surgery: A Practical Guide [Internet]. Cham: Springer International Publishing; 2017 [cited 2022 Sep 19]. p. 1–17. Available from: https://doi.org/10.1007/978-3-319-52210-4_1

Aboulghar MM. Ultrasound monitoring for ovulation induction: pitfalls and problems. In: Rizk B, Aboulghar M, editors. Ovarian Stimulation [Internet]. Cambridge: Cambridge University Press; 2010 [cited 2023 Oct 19]. p. 217–32. Available from: https://www.cambridge.org/core/books/ovarian-stimulation/ultrasound-monitoring-for-ovulation-induction-pitfalls-and-problems/CEAC575EB4F263688A70F88114769611

Jansen CA, van Os HC. Value and limitations of vaginal ultrasonography--a review. Hum Reprod Oxf Engl. 1989 Nov;4(8):858–68.

Manu M, Anand G. A review of medical device regulations in India, comparison with European Union and way-ahead. Perspect Clin Res. 2022;13(1):3–11.

Su HW, Yi YC, Wei TY, Chang TC, Cheng CM. Detection of ovulation, a review of currently available methods. Bioeng Transl Med. 2017;2(3):238–46.

Martinez AR, van Hooff MHA, Schoute E, van der Meer M, Broekmans FJM, Hompes PGA. The reliability, acceptability and applications of basal body temperature (BBT) records in the diagnosis and treatment of infertility. Eur J Obstet Gynecol Reprod Biol. 1992 Nov;47(2):121–7.

Rollason JC, Outtrim JG, Mathur RS. A pilot study comparing the DuoFertility® monitor with ultrasound in infertile women. Int J Womens Health. 2014 Jul 16;6:657–62.

Lagrone LN, Sadasivam V, Kushner AL, Groen RS. A review of training opportunities for ultrasonography in low and middle income countries. Trop Med Int Heal. 2012;17(7):808–19.

Ali R, Gürtin ZB, Harper JC. Do fertility tracking applications offer women useful information about their fertile window? Reprod Biomed Online [Internet]. 2021;42(1):273–81. Available from: https://doi.org/10.1016/j.rbmo.2020.09.005

Johnson S, Marriott L, Zinaman M. Can apps and calendar methods predict ovulation with accuracy?. Current Medical Research and Opinion. 2018 Sep 2;34(9):1587-94.