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Hormonal Smartphone Diagnostics.

P R Matías-García¹, J L Martinez-Hurtado², A Beckley³

¹Institute of Medical Informatics, Biometry and Epidemiology (IBE), Ludwig-Maximilians-Universität München, Munich, Germany.

Methods in Molecular Biology (Clifton, N.J.)

|January 31, 2018

Summary

This summary is machine-generated.

This study introduces a mobile technology method for quantitative analysis of hormonal test strips, improving interpretation of results. This innovation enhances early diagnostics and fertility monitoring using urine samples.

Keywords:

Application Diagnostics Hormones Medical Mobile Ovulation PdG Progesterone Quantitative assays Smartphone

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Area of Science:

Biomedical Diagnostics
Mobile Health Technology
Reproductive Endocrinology

Background:

Point-of-care diagnostics are crucial for healthcare delivery.
Hormonal diagnostics enable monitoring of physiological changes.
Urine-based hormone tests, like lateral flow immunoassays, are common for early diagnostics but often lack quantitative interpretation.

Purpose of the Study:

To present a novel method for quantitative reading and interpretation of hormonal test strips using mobile technologies.
To demonstrate the application of this method for detecting pregnanediol glucuronide (PdG) in urine.
To correlate PdG levels with ovulation and the female fertility cycle.

Main Methods:

Development of a mobile technology-based system for quantitative analysis of hormonal test strips.
Application of the method for detecting pregnanediol glucuronide (PdG), a progesterone metabolite, in urine samples.
Validation of the quantitative results against established diagnostic parameters related to the fertility cycle.

Main Results:

Successful quantitative detection and interpretation of hormonal test strips using mobile technology.
Demonstrated accurate measurement of urinary pregnanediol glucuronide (PdG).
Established a correlation between quantitative PdG levels and key fertility cycle events, including ovulation.

Conclusions:

Mobile technology offers a viable solution for quantitative, objective interpretation of hormonal test strips.
This method enhances the utility of urine-based hormonal diagnostics for early detection and monitoring.
The developed approach provides a valuable tool for fertility tracking and understanding hormonal fluctuations.