Z.M. Yuldashev1, Е.А. Semenova2, I.P. Korneeva3, Yu.О. Bobrova4

1–4 St. Petersburg State Electrotechnical University "LETI" (Saint Petersburg, Russia)
 

The problem of developing a system for monitoring the health state of people with chronic non-communicable disease (CNCD) is considered. To improve the effectiveness of medical care for such patients, it is proposed to use long-term remote monitoring of their health outside the medical institution and, based on the analysis of personalized patterns of dynamics of diagnostically significant indicators for the state of remission and exacerbation of the disease, to ensure the possibility of detecting its exacerbation at an early stage of development.

The aim of the work is to develop a system for remote long–term monitoring outside a medical institution of the health state of patients with a chronic non-communicable disease to detect its exacerbation at an early stage.

The system of long-term remote monitoring outside the medical institution of the health state of patients with a chronic disease allows identifying individual features of the course of a chronic non-communicable disease based on in-depth analysis of monitoring data and personifying models describing the state of remission and exacerbation of the disease of a particular patient in a multidimensional space of diagnostically significant indicators. The possibility of predicting and early detection of an exacerbation of the disease is based on an assessment of the rate of displacement of the vector of the patient's current state of health from the area of remission to the area of exacerbation of the disease.

The practical value of the research result lies in the development of the structure of the system and methods of remote long-term monitoring of the health status of patients with chronic non-communicable disease, ensuring an improvement in the quality of medical care for patients with CNCD.

Yuldashev Z.M., Semenova E.A., Bobrova Yu.O., Korneeva I.P. Remote monitoring of the health state of people with a chronic disease to detect its exacerbation at an early stage. Biomedicine Radioengineering. 2023. V. 26. № 2. P. 5–11. DOI: https:// doi.org/10.18127/j15604136-202302-01 (In Russian)

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