Latest research on core body temperature (CBT) monitoring has showed great benefits for healthcare professionals. Converging technologies are proving their value in continuous monitoring of patients in between appointments. In the last few years medicine has been able to harness the power of smart devices to make real differences to lives, whether in diagnostics, disease prevention and in helping to observe and manage the COVID19 pandemic.
One of the early uses of smartphone technology was in ovulation monitoring. It was a good fit as a degree of interaction was required with the smartphone by entering data and understanding the interpretations of that data in order to make decisions. Most smart ovulation monitoring systems rely on inputting data, which arises from urine testing in the home setting. However, as all health care professionals know chemicals don’t always translate into a clear clinical picture and nuances can be lost1.
CBT measurement is another approach to ovulation monitoring, which offers the benefit of measuring a clinical rather than chemical parameter. Measuring CBT in order to determine the ovulation window is a traditional approach. However, the main problems experienced in the past were lack of precision as the differences in CBT vary by only about 0.5 degrees Celsius. There were also wide variations in cycle length between females and the ovulation window can sometimes wander around.
Converging technologies can overcome these issues and offers some exciting new possibilities in terms of diagnostics and patient management.
An example of this is the OvuSense and OvuSense Pro ovulation home monitoring device2.
OvuSense and OvuSense Pro
OvuSense uses measurements of CBT, taken as overnight vaginal temperature readings. This is achieved via an easy-to-use sensor, much like a tampon. This collects data that is then synched with a smartphone. This can then predict ovulation using current cycle data, confirm ovulation and produce detailed cycle patterns. This data then shows what is happening to the level of progesterone throughout each cycle.
It provides a high level of accuracy and predictive value3:
- Positive predictive value of ovulation 24 hours in advance of 96%
- Accuracy to within 0.003 degrees Celsius.
The standard version of OvuSense can be used to track ovulation and observe cycle patterns by eye.
OvuSense Pro is a subscription add on available to OvuSense users. It provides in-depth cycle pattern analysis, automatically flagging each cycle pattern from types already identified, aiding diagnosis and treatment of ovulatory issues. OvuSense Pro also allows users to share their data with their healthcare professionals through a dedicated encrypted online portal.
What types of cycle pattern analysis can be flagged from types already identified?
It’s best to illustrate this with an example. Here is an atypical cycle pattern flagged by OvuSense – identified as the Crash to Baseline pattern4:
- Blue line: shows the best representative raw CBT value produced by the OvuSense algorithm for each set of overnight measurements, taken every 5 minutes.
- Blue shading: OvuSense detected day of ovulation.
- Green line: this is the smooth weighted average CBT curve as used by the OvuSense algorithm to predict ovulation up to 24 hours in advance using this current cycle’s data, and then confirm ovulation.
- Green shading: the ovulation window
- Grey line: the typical pattern, which might have been expected for this cycle taking into account an expected textbook middle of the cycle ovulation.
Explanation: this anomaly could possibly be due to high progesterone levels early in the cycle. One of the conditions that could cause this might be polycystic ovary syndrome (PCOS), a leading cause of infertility.
There are plenty of other atypical patterns which the system is programmed to identify:
In each case key information is provided:
- What is it?
- How common is it?
- Why does it happen?
- How can I see it?
- What does it mean?
- What can be done about it?
Given this, OvuSense is an excellent example of what at-home diagnostic tools now look like in the 21st Century! As new technologies emerge such as artificial intelligence, they will also be seamlessly integrated into the converged technology matrix to create ever more powerful solutions for diagnosis and management of healthcare issues.
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1. P. G. McGovern, P G et al. 2004. Absence of secretory endometrium after false-positive home urine luteinizing hormone testing. Fert Stert. November 2004. Volume 82. Issue 5. Pages 1273–1277
3. S. Papaioannoua, B.H. Al Wattara, R.C. Milnesc, T.G. Knowlesb. 2013. Quality index assessment of vaginal temperature-based fertility prediction and comparison with luteinising hormone testing, ultrasound folliculometry and other home cycle monitors. Fert Stert. September 2013. Volume 100. Issue 3, Supplement. Pages S326–S327
4. Hurst B, et al. Atypical vaginal temperature patterns may identify subtle, not yet recognized, causes of infertility. Poster presented at the ASRM Congress. 12-16 October 2019. Philadelphia, USA. https://www.ovusense.com/uk/P345-Atypical-vaginal-temperature-patterns-may-identify-subtle-not-yet-recognised-causes-of-infertility-ASRM-2019.pdf