The goal of the project is a telemedicine network of smart in-home monitoring systems for outpatient pregnancy surveillance to ensure early detection of pregnancy complications and fetal pathologies, as well as ubiquitous information support of pregnancy care both antenatal and intrapartum.

The solution of perinatal morbidity and mortality problem lies in the development of an information technology for large-scale eHealth-enabled management of pregnancy, making use of personal mobile web monitors, cloud computing and artificial intelligence. The solution leads to halving the indices of perinatal morbidity and mortality, as well as the costs of pregnancy care at the same time. Lowering the costs of care in turn ensures the investment attractiveness of the eHealthcare services, and makes them affordable to low budget care providers. The advances of the technology are substantiated by the results already obtained. The concept of large-scale eHealth pregnancy management, making use of mobile/ wearable personal monitors, artificial intelligence and cloud computing is first proposed.

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The research is aimed at reducing perinatal morbidity by prevention of pregnancy complications with largescale e-health fetal monitoring. An approach with multifunctional ultrasonography is proposed by using an mhealth Doppler web monitor. The technology should meet with high acceptance in under-resourced settings.A. P. Kazantsev is with the