Hardware and software complex for remote monitoring and control of a pregnant woman's health state

Introduction: The problem of remote monitoring of people's health has become especially urgent nowadays due to the rapid spread of dangerous infectious and viral diseases, such as COVID-19. This period was especially difficult for pregnant women. According to Rosstat statistics, in 2020, maternal mortality in Russia increased by 24.4% compared to 2019 and reached 11.2 per 100,000 newborns. This is the worst level since 2013. In the current conditions, there is a necessity for developing remote monitoring systems which allow you to check the health status of a pregnant woman remotely using tools outside a medical institution. Purpose: To develop the structure and validate the choice of elements for a hardware and software complex which would perform remote monitoring outside a medical institution and assess the condition of pregnant women during their active life. Results: An automated questionnaire for pregnant women has been developed in accordance with the methodological recommendations of the Ministry of Health of the Russian Federation, providing a quantitative assessment of the current state of a pregnant woman in order to study the dynamics of her health. Based on the results of instrumental studies, according to 30 factors of patient's body functioning and the questionnaire data, a set of diagnostically significant indicators was developed. For each of them, a range of values was specified (norm, alarm, pathology). We have developed an experimental sample of the hardware and software complex and tested its functioning, particularly the modes of taking biomedical data by urine tests. The algorithms for processing and analysis of biomedical data have been experimentally studied in order to confirm the validity of the proposed solutions. Practical relevance: The results of the studies allow us to affirmatively answer the question about the possibility of remote monitoring outside a medical institution and assessing the health state of a pregnant woman in order to predict pregnancy complications, as well as to validate the choice of measuring channels for recording a complex of biomedical signals and data, and the choice of algorithms for information processing and analysis.