An inexpensive smartphone-based device for point-of-care ovulation testing

Lab Chip. 2018 Dec 18;19(1):59-67. doi: 10.1039/c8lc00792f.

Abstract

The ability to accurately predict ovulation at-home using low-cost point-of-care diagnostics can be of significant help for couples who prefer natural family planning. Detecting ovulation-specific hormones in urine samples and monitoring basal body temperature are the current commonly home-based methods used for ovulation detection; however, these methods, relatively, are expensive for prolonged use and the results are difficult to comprehend. Here, we report a smartphone-based point-of-care device for automated ovulation testing using artificial intelligence (AI) by detecting fern patterns in a small volume (<100 μL) of saliva that is air-dried on a microfluidic device. We evaluated the performance of the device using artificial saliva and human saliva samples and observed that the device showed >99% accuracy in effectively predicting ovulation.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Artificial Intelligence
  • Equipment Design
  • Female
  • Humans
  • Models, Biological
  • Ovulation Detection / instrumentation*
  • Ovulation Detection / methods
  • Point-of-Care Testing*
  • Saliva / chemistry
  • Smartphone*
  • Young Adult