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

Authors: Potluri, Vaishnavi; Kathiresan, Preethi Sangeetha; Kandula, Hemanth; Thirumalaraju, Prudhvi; Kanakasabapathy, Manoj Kumar; Kota Sai Pavan, Sandeep; Yarravarapu, Divyank; Soundararajan, Anand; Baskar, Karthik; Gupta, Raghav; Gudipati, Neeraj; C Petrozza, John; Shafiee, Hadi

Published In Lab Chip, (2018 Dec 18)

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.

PubMed ID: 30534677

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