Novel Technique for Confirmation of the Day of Ovulation and Prediction of Ovulation in Subsequent Cycles Using a Skin-Worn Sensor in a Population With Ovulatory Dysfunction: A Side-by-Side Comparison With Existing Basal Body Temperature Algorithm and Vaginal Core Body Temperature Algorithm - B. S., Hurst; K., Davies; R. C., Milnes; T. G., Knowles; A., Pirrie (Frontiers in Bioengineering and Biotechnology, 2022)
Objective: Determine the accuracy of a novel technique for confirmation of the day of ovulation and prediction of ovulation in subsequent cycles for the purpose of conception using a skin-worn sensor in a population with ovulatory dysfunction. Methods: A total of 80 participants recorded consecutive overnight temperatures using a skin-worn sensor at the same time as a commercially available vaginal sensor for a total of 205 reproductive cycles. The vaginal sensor and its associated algorithm were used to determine the day of ovulation, and the ovulation results obtained using the skin-worn sensor and its associated algorithm were assessed for comparative accuracy alongside a number of other statistical techniques, with a further assessment of the same skin derived data by means of the ‘three over six’ rule. A number of parameters were used to divide the data into separate comparative groups and further secondary statistical analyses were performed. Results: The skin-worn sensor and its associated algorithm (together labelled ‘SWS)’ were 66% accurate for determining the day of ovulation (±1 day) or the absence of ovulation, and 90% accurate for determining the fertile window (ovulation day ±3 days) in the total study population in comparison to the results obtained from the vaginal sensor and its associated algorithm (together labelled ‘VS’). Conclusions: SWS is a useful tool for confirming the fertile window and absence of ovulation (anovulation) in a population with ovulatory dysfunction, both known and determined by means of the timing of ovulation. The body site where the skin-worn sensor was worn (arm or wrist) did not appear to affect the accuracy. Prior diagnosis of known causes of ovulatory dysfunction appeared to affect the accuracy to a lesser extent than those cycles grouped into late ovulation and ‘early and normal ovulation’ groups. SWS is a potentially useful tool for predicting ovulation in subsequent cycles, with greater accuracy obtained for the ‘normal ovulation’ group.