Smartphone-based Colorimetric Analysis of Urine Dipsticks for At-Home Prenatal Care
The early detection of maternal and fetal diseases and ensuring maternal and fetal health are the
main objectives of prenatal care. An essential part of prenatal care are laboratory diagnostics,
including the examination of urine samples, which are conducted at regular intervals as part of
the general examination repeatedly scheduled in prenatal care . Urine tests based on test strips
belong to the so-called Point of Care Testing or patient-oriented immediate diagnostics, which are
playing an increasing role in the healthcare system and are also benetting from the progressive
integration of smartphones .
In this research work, a method is to be developed that automates the evaluation of urine test
strips with the aid of a smartphone, allowing the patient to perform the examination complety
from home. Previous studies showed, that the potential of smartphones for urinalysis is high and
an evaluation without further equipment is feasible . Some studies already investigated the
inuence of varying illumination and dierent smartphones [4, 5]. However, little work regarding
pregnant women, obstetrical care, a large study population as well as the respective feasibility
and usability questions exists in literature.
Therefore the aim of this research work is to evaluate the feasibilty of an automated colorimetric
analysis of urine dipsticks using image processing and/or machine learning and a respective
smartphone application for use in a home environment within prenatal care.
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