A System for Remote Monitoring of Pregnant Women's Health State

and Pregnancy Complications Prediction

Inna Korneeva

, Kristina Kramar

, Evgeniia Semenova

and Zafar Yuldashev

Saint Petersburg Electrotechnical University "LETI", 5, Professora Popova St., Saint-Petersburg, Russian Federation

Keywords: Remote Monitoring, Instrumental Methods, Complex of Biomedical Signals and Indicators, Assessment of

the Current State, Dynamics Analysis, Short-Term Predicting, Pregnancy Complication.

Abstract: The development results of the system for remote monitoring of pregnant women's health state and pregnancy

complications prediction are discussed. A set of diagnostically significant indicators has been substantiated

and formed to assess the current state, monitoring and control of pregnant women health and prediction of

pregnancy complications. Four groups of indicators showing the functioning of cardiovascular and endocrine

systems of the body, biochemical urine indicators, and indicators taking into account subjective assessment

of the pregnancy course have been identified. To assess these indicators, a set of biomedical signals is

proposed, signal acquisition tools and an automated questionnaire of a pregnant woman was suggested

according to experts’ recommendations. A method for forming an integral assessment by groups of indicators,

considering the risk of pregnancy complications and weight of a diagnostically significant indicator, and a

method for short-term predicting of pregnancy complications based on the dynamics analysis of various

groups of integral indicators are developed. An experimental sample of the system was developed and its

individual functions were clinically tested in order to assess the correctness of the proposed solutions. The

results of the approbation are discussed.

1 INTRODUCTION

The problem of remote health monitoring has become

very important for pregnant women due to the

negative impact of viral diseases on the course of

pregnancy. Against the background of the risks of

pregnancy complications due to existing chronic non-

infectious diseases, such as hypertension, diabetes,

chronic obstructive pulmonary diseases, in the

context of the Covid-19 pandemic, the risks of

pregnancy complications increase sharply (Villar et

al, 2021). The combined impact of negative factors

has caused increased maternal mortality in almost all

countries of the world. This trend has especially

intensified in countries with a high incidence of

Covid-19. The WHO statistics show the increase in

maternal mortality in a number of countries up to 30%

(Yap et al, 2020). Under the current conditions, the

most effective way to reduce maternal mortality is to

https://orcid.org/0000-0002-7587-5317

https://orcid.org/0000-0002-0122-9005

https://orcid.org/0000-0001-5608-3544

https://orcid.org/0000-0003-1075-3420

use remote monitoring of pregnant women's health

state outside a medical institution and prediction of

pregnancy complications for emergency medical care

(Ryu et al, 2021; Hema et al, 2020). The remote

dynamics monitoring of a pregnant women's health

state using instrumental methods and tools and an

automated questionnaire designed to quantify the

dynamics of subjective feelings of a pregnant woman

about her state of health, allows identifying negative

trends in the health state of a pregnant woman and

predicting pregnancy complications in the short term.

The study objective is to develop instrumental

methods and system structure for remote monitoring

of a pregnant women's health state outside a medical

institution in conditions of active life and predicting

pregnancy complications.

The tasks of the study are as follows:

1. Justification and selection of a set of

diagnostically significant indicators and signs

306

Korneeva, I., Kramar, K., Semenova, E. and Yuldashev, Z.

A System for Remote Monitoring of Pregnant Women’s Health State and Pregnancy Complications Prediction.

DOI: 10.5220/0011011500003123

In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2022) - Volume 1: BIODEVICES, pages 306-314

ISBN: 978-989-758-552-4; ISSN: 2184-4305

showing the health state and the course of

pregnancy;

2. Justification and selection of a complex of

biomedical signals required for the assessment

of diagnostically significant indicators, methods

of their acquisition and registration in remote

monitoring conditions outside the medical

institution;

3. Development of a method for remote

monitoring of pregnancy and complications

predicting;

4. Justification and development of the structure of

the remote monitoring system and prediction of

pregnancy complications;

5. Clinical approbation of methods for recording

signals outside a medical institution and

predicting health state conditions using an

experimental sample of the developed system.

Methods and materials of the study. To assess,

monitor and control pregnant women's current health

state, instrumental research methods were used with

small-sized portable devices: a biochemical analyzer

for evaluating 11 urine indicators, a device for

assessing blood sugar levels, an automatic

coagulometer, a blood pressure meter, a spirometer

and a pulse oximeter. When monitoring and

controlling the health state of a pregnant woman and

predicting the risk of pregnancy complications, the

assessment frequency of the current health state was

determined based on the significant indicators

dynamics. To ensure high accuracy of the short-term

prognosis of pregnancy complications, the trend

equations of indicators were determined, after each

next stage of assessing the current state, the trend

equation was corrected. The experimental

approbation of the proposed methods and remote

monitoring system was carried out under the

supervision of doctors with the involvement of

patients who were at risk of pregnancy complications.

2 SOLVING RESEARCH

PROBLEMS

2.1 Justification and Selection of a Set

of Diagnostically Significant Health

State Indicators

To carry out remote monitoring of a pregnant

women's health state and predict pregnancy

complications, a number of diagnostically significant

indicators of the state of vital body systems were

selected, changes in which primarily signal the

presence of pathological processes in the pregnant

woman's body. These indicators were selected

considering the opinion of practicing specialists in the

field of obstetrics and gynecology.

After studying of a pregnant women's health state

parameters which must be monitored during

pregnancy, a set of diagnostically significant

indicators was formed. They can be divided into four

groups:

1. The first group includes information about the

health of a pregnant woman, parameters of her

body, information about bad habits, allergic

reactions, past illnesses, family and obstetric

and gynaecological history. This information is

necessary in order the doctor has a general

vision about the health of a pregnant woman and

characteristics of her body. This knowledge will

make it possible to conduct pregnancy more

effectively, consider cause-and-effect

relationships, as well as prescribe medications,

considering all characteristics of the patient.

2. The second group includes the results of

analytical studies. Conducting a biochemical

blood test allows to detect health disorders at an

early stage. The key indicators are the level of

haemoglobin, platelets, leukocytes, glucose and

the level of blood clotting. These indicators help

to identify such common diseases in pregnant

women as anaemia, thrombosis, and gestational

diabetes mellitus. It is also extremely important

to conduct a biochemical analysis of urine

which allows determining the level of protein in

the urine (Korneeva, 2021). Proteinuria is one of

the symptoms of such a dangerous disease as

preeclampsia, which is associated with high

maternal and perinatal mortality. Also, the

biochemical analysis of urine determines the

level of glucose, bilirubin, leukocytes, and

relative density of biological fluids. These

indicators contribute to the early identification

of other dangerous diseases and clarify

(supplement) the results of a biochemical blood

test.

3. The third group includes indicators obtained

during instrumental studies of the functional

state of the main body systems. First of all, it is

necessary to monitor the dynamics of changes in

the performance of the cardiovascular system.

During pregnancy, significant changes occur in

the cardiovascular system, its load increases

significantly, therefore it is necessary to monitor

the reaction of blood vessels and the heart,

especially in the case of various cardiovascular

diseases before pregnancy. Blood pressure and

A System for Remote Monitoring of Pregnant Women’s Health State and Pregnancy Complications Prediction

307

heart rate measurements are used for daily

monitoring, and if deviations are detected,

extended ECG studies are performed to make a

diagnosis (Semenova et al, 2020). Due to the

increase in oxygen demand, the load on the

respiratory system also increases; this justifies

the need to monitor the dynamics of the

respiratory system state, primarily the lungs

vital capacity. Together with the study of

functional state indicators of the respiratory

system, it is necessary to register the oxygen

level in the patient's blood, since its decrease is

one of the main symptoms of an ongoing

infectious disease. In addition, it is necessary to

monitor the body temperature of a pregnant

woman, since its increase is an adverse

symptom that may indicate the onset of

infection.

4. The fourth group includes indicators of a

pregnant women's current health state, which

cannot be quantified using medical devices.

Monitoring of these indicators is necessary

when the results of an instrumental examination

do not reveal conditions that threaten life and

health of a pregnant woman, although she draws

the doctor's attention to a feeling of discomfort.

To eliminate uncertainty in such situations, the

doctor tries to assess the subjective feelings of

the pregnant woman's condition. An example of

such indicators is the degree of swelling, which

may be a sign of thrombosis or preeclampsia,

the severity of toxicosis and the presence of

gynaecological discharge, which may be a

symptom of miscarriage.

The selected set of diagnostically significant

indicators and signs will be used for the integral

assessment of a pregnant women's health state, it will

help to identify the presence of diseases in the early

stages and predict pregnancy complications.

2.2 Justification and Selection of a

Complex of Biomedical Signals

Necessary for the Assessment of

Diagnostically Significant

Indicators

To form a complex of diagnostically significant

indicators characterizing a pregnant women's current

health state, data from analytical and instrumental

studies are required.

Analytical studies in the clinic include the

assessment of the biochemical studies complex of the

blood and urine of a pregnant woman. During the

research, the presence of markers of various pregnancy

complications is analyzed, as well as the risks are

calculated. In the conditions of remote monitoring, it is

possible to conduct express analysis of biochemical

parameters, namely: general biochemical analysis of

urine by dry chemistry, as well as analysis of blood

glucose, analysis of blood clotting indicators based on

coagulometry. Analytical studies are used primarily to

assess metabolic processes in the body and to identify

disorders at early stages.

Instrumental research methods are used to assess

the functional state of the main body systems of a

pregnant woman. To assess the functional state of the

cardiovascular system, a multifunctional wearable

heart monitor is used, which provides the acquisition

and registration of the ECG signal, blood pressure

monitoring. It is used to assess the heart rate and heart

rate variability at different levels of physical activity,

the dynamics of blood pressure. A portable spirometer

and pulse oximeter are used to study the state of the

respiratory system. They provide an assessment of

characteristics of the respiratory cycle and the

dynamics of blood oxygen saturation. The assessment

of the endocrine system state is based on glucose levels

in the blood and urine of a pregnant woman and their

comparison with reference indicators.

An important condition when choosing measuring

channels and technical means for implementation of

measurements is their compliance with the standards

to the equipment for the provision of medical services

in the field of obstetrics and gynaecology, which are

regulated by regulatory documents, the certificate

availability of state registration of a medical device

on the territory of the country.

In accordance with the requirements, the

following medical devices are used in the measuring

channels:

-portable biochemical urine analyzer;

-portable biochemical blood clotting analyzer;

-portable heart monitor with automatic tonometer;

-portable spirometer and pulse oximeter;

-portable blood glucose meter.

The listed devices together provide monitoring

and control of a pregnant women's health state

according to the indicators listed above.

2.3 Development of a Method for

Remote Monitoring of Pregnancy

and Complications Predicting

Remote monitoring and control of a pregnant women's

health state is carried out by periodically taking and

registering biomedical signals and data outside the

RMHM 2022 - Special Session on Remote Management and Health Monitoring

308

medical institution, assessing the current condition of a

pregnant woman by groups of diagnostically

significant indicators showing the state of

cardiovascular, respiratory and endocrine systems,

biochemical indicators and markers of specific

complications of pregnancy. Additionally, the

assessment of the health state dynamics of a pregnant

woman is carried out using an automated questionnaire

developed on the basis of the approved form of a

pregnant woman examination recommended by

medical experts (Kramar et al, 2021).

Monitoring of a pregnant women's health state is

carried out using the adaptive sampling method. The

method consists in changing the frequency of data

collection and subsequent assessment of the

condition, based on the dynamics analysis of a

complex of diagnostically significant health

indicators, as well as the combined manifestation of

signs of pregnancy complications (Adaptive

sampling. US patent US2011/0066053A1). As soon

as any of the monitored indicators reaches the norm

limit it must be carefully monitored and the time

intervals between successive measurements should

be shortened. This approach is used to correct the

trend equation in a timely manner and ensure high

accuracy in predicting pregnancy complications.

Algorithms for processing the received data and

subsequent assessment of the current state and

dynamics monitoring of the pregnant woman's

condition are based on the use of distributed signal

processing technology. The first part of calculations

is performed on a pregnant woman's wearable

computer (smartphone), which is an aggregator of

biomedical signals recorded from the patient from

various sources of acquisition and registration of

biomedical signals and data. The pregnant woman's

wearable computer structures information and

transmits it to the server of a medical institution. The

second part of calculations related to the assessment

of the patient's current condition, monitoring and

control of the health state, and predicting pregnancy

complications is performed on the server of the

medical institution, and the results are transmitted to

the wearable computer of the doctor in charge.

To assess the current health state of a pregnant

woman the significance of each indicator is

preliminarily assessed according to a set of

diagnostically significant indicators. To do this, the

method of hierarchy analysis is used, which consists in

a hierarchical representation of a group of indicators

that determine the health state of a pregnant woman.

The decomposition of each group of indicators into

simpler components is performed, i.e. into point

indicators, and further pairwise comparison of specific

medical indicators by a specialist in obstetrics and

gynaecology. As a result, the relative intensity of the

indicators interaction in the hierarchy is expressed

numerically, i.e. the influence of each indicator on

general health of a pregnant woman is indicated. The

chosen method has high universality, it is easy to use

but it requires deep involvement of experts in solving

the problem, which reduces the likelihood of errors

when using this method.

The algorithm for calculating weight coefficients

using the hierarchy analysis method consists of the

following steps (Schmidt et al, 2015):

1. Formation of goals hierarchy. A hierarchy is

formed, the top of which is the goal to be

achieved, or the essence of the problem. In our

case, the top of the hierarchy is the assessment of

a pregnant women's health state. The following

levels present criteria that directly affect the

achievement of the goal, i.e. groups of

diagnostically significant indicators and specific

indicators included in these groups.

2. Pairwise comparison of indicators by importance.

For comparison, a ten-level scale of relative

importance of elements is used, with the help of

which the expert alternately compares the

significance of each indicator relative to the

others.

3. Calculation of local priority vectors. At this stage

of the calculation, a preliminary conclu-sion is

made about which of indicators is the most

significant for assessing the health state.

4. Checking the consistency of local priorities. At

this stage, the consistency ratio (CR) is

calculated. If CR > 0.1, it is stated that the expert's

judgments, on the basis of which the comparison

of indicators was carried out, are inconsistent,

which means that the second comparison should

be carried out. Otherwise, the expert's judgments

are accepted and the weight coefficients obtained

in paragraph 3 are used for further operation of

the algorithm.

Thus, it is possible to calculate the weight

coefficients of each diagnostically significant indicator

and assess their impact on the current health state of a

pregnant woman. The complex consisting of more than

30 diagnostically significant indicators is used for an

integral assessment of the pregnant woman health

state.

According to the described method, the weights of

the first hierarchy level of diagnostically significant

indicators were calculated, i.e. the influence of each

group of daily monitored indicators on the health of a

pregnant woman was evaluated (Table 1).

A System for Remote Monitoring of Pregnant Women’s Health State and Pregnancy Complications Prediction

309

Table 1: Weight coefficients of the top level of the hierarchy.

Top level Fetal

movements

Physiological

indicators

Painful

syndrome

Nausea and

vomiting

Pathological

secretions

Weights

Fetal movements 1 3 1 3 1 0,27

Physiological indicators 1/3 1 1/3 3 1/3 0,12

Painful syndrome 1 3 1 5 1 0,29

Nausea and vomiting 1/3 1/3 1/5 1 1/3 0,06

Pathological secretions 1 3 1 3 1 0,26

CR = 0,02

The obtained values of the weight coefficients are

used in the automated questionnaire for the integral

assessment of a pregnant women's health state.

To monitor the current health state of a pregnant

woman, it is necessary to consistently compare the

values of each monitored indicator with the norm

level and, if the value of the controlled indicator

exceeds the critical level, send an alarm signal to the

doctor. A decision tree is used to form rules for

comparing the values of diagnostically significant

indicators with threshold levels. The decision tree is

a decision support tool used to identify logical

patterns in data. The rule by which the decision tree

functions in the trivial case is represented as "If A,

then B". If there is more than one condition in the rule,

then it takes the following form:

"If <condition 1> ∩ <condition> ∩ <condition n>,

then <objective function>"

Moving along the tree from the upper level to the

lower one, it is possible to determine the logical rules

of the system functioning. This method was chosen

due to the simplicity of its use and interpretation,

since making a decision using a decision tree repeats

the logic of a doctor when making a diagnosis.

A fragment of the decision tree, which is used in

the daily assessment of a pregnant women's health

state is shown in Fig. 1.

If any indicator exceeds the value of the "norm",

this indicator is classified as "pathology" (marked in

red) and is included in the report on the current health

state of a pregnant woman, which will be sent to the

attending physician along with an alarm. If the

indicator deviates slightly from the norm or the

indicator value is found on the norm-pathology

border, it is marked in yellow, a report on the current

state of health is also sent to the attending physician.

In this case, close monitoring of the health status of a

pregnant woman is required, repeated verification of

this indicator after a while and consultation with the

attending physician via cellular communication. If all

indicators correspond to normal values, a pregnant

women's current health state is classified as "normal",

the generated report with the current values of

indicators is stored in the database and can be

obtained by the attending physician upon request.

Figure 1: Part of the decision tree used in the daily

assessment of a pregnant women's health state.

Pain in the lower

abdomen

Yes

Nausea

Yes

Vomiting (times a

day)

Body temperature

>37,2

Signs of SARS Signs of SARS

Yes

o Yes

…

5-10 <5

<37,2

RMHM 2022 - Special Session on Remote Management and Health Monitoring

310

To predict the dynamics of a pregnant women's

health state, the method of analyzing a time series of

states based on the construction of a trend equation is

used. Predicting is based on the assumption that the

development pattern observed in the past will

continue in the predicted future. At the same time, the

level of the time series is formed under the influence

of many factors, but the influence of each of them is

not singled out separately. In this case, the

development trend is not related to the factor, but to

the time period. Predicting is carried out by groups of

indicators. Before you start predicting, you need to

make sure that the data are normalized. Next, an

extrapolation procedure is carried out, that is, an

extension for the future of the trend observed in the

past. Further, by substituting the prediction period

into the trend equation, a point estimation of the

prediction is obtained at a specific time in the future,

and the boundaries of a possible change in the

prediction indicator are determined. The prediction

result is also sent to the doctor, in addition to the main

report on the patient's current condition.

2.4 Justification and Development of

the Structure of the Remote

Monitoring System and Prediction

of Pregnancy Complications

For remote monitoring of a pregnant woman's health

state and prediction of pregnancy complications, the

system presented in Figure 2 is proposed.

The structure of the system consists of several

levels (Yuldashev et al, 2017). At the first level,

biomedical signals and data are collected and

recorded outside the medical institution, providing a

comprehensive assessment of the current state of the

body on the principles of systemic medicine. At the

same time, data is collected on more than 30

indicators, including indicators of the functioning of

various body systems, such as the cardiovascular and

endocrine systems, the respiratory system, as well as

data from biochemical studies showing the dynamics

of biochemical parameters of urine and blood

clotting. At this stage, it becomes possible to identify

individual features of the functioning of the body at

all stages of pregnancy with the combined

manifestation of various chronic diseases and

exposure to external pathogens.

At the second level, information about the current

health state of a pregnant woman is structured,

considering the degree of diagnostic significance of

indicators, correction of individual norm indicators,

considering the combined manifestation of several

factors of exacerbation of the disease, and a

formalized description of a pregnant women's health

state is compiled based on a set of diagnostically

significant indicators. If necessary, biomedical

signals received from measuring channels are pre-

processed. The complex of diagnostically significant

indicators is divided into groups according to the

level of importance.

Structuring of information at the second level of

the system is carried out in order to present it to the

doctor in a form convenient for subsequent analysis

and to reduce the level of medical error. Using of the

automated questionnaire allows to quantify the

dynamics of the pregnant woman's condition. The

data of the automated survey of a pregnant woman

consist of both rank variables showing her feelings

about the signs of pregnancy, which cannot be

quantified, and quantitative variables obtained using

instrumental means. In the process of processing

the results of an automated survey, rank variables

are converted into quantitative ones using methods

of qualimetry, and an integral self-assessment of

the state is formed (Mabikwa et al, 2017).

Figure 2: Generalized structure of the system for remote monitoring of pregnant women's health state.

Portable medical

devices

Smart

hone

Level №2

Serve

Level №3

sician's

computer

Level №1

Level №4

Channel

WWAN

Channel

WWAN

Channel

Bluetooth

Channel GSM

Registration of

iomedical si

nals

Assessment of a pregnant

woman

s health indicators

Lon

-term monitorin

and predicting of health state

Making a decision by a

sician

A System for Remote Monitoring of Pregnant Women’s Health State and Pregnancy Complications Prediction

311

This quantitative assessment is necessary solely to

reflect the dynamics of the health status of a pregnant

woman in some metric scale. The answers obtained

allow the doctor to assess the subjective state of the

pregnant woman, which is an important diagnostic

sign of a number of diseases, since in some cases it is

impossible to fix the presence of pathology with the

help of available tools.

To predict the dynamics of the condition and the

possible development of pregnancy complications, a

trend line is preliminarily constructed, which allows

predicting the borderline state and the state of

complications of pregnancy, considering the

combination of the influence of factors aggravating

the complication of its course. Predicting is

performed by groups of diagnostically significant

indicators with a frequency sufficient to obtain

sufficient results.

It is known that for the state of the physiological

norm, biomedical indicators showing the processes

occurring in the human body describe oscillatory

processes (daily, weekly, monthly) within the

individual norm. It is characterized by lower and

upper boundaries. These processes can be described

by a set of harmonic functions, each of which will

describe the dynamics of indicators during the day,

week, month. When exposed to any factor that causes

a complication of the course of pregnancy, there will

be a trend in the dynamics of the indicator. It will

show the transition from the state of an individual

norm to a qualitatively new state. In the first

approximation, this trend can be described either by

an exponential dependence, in which the time

constant of the exponent will show the duration of the

transition process, or by a Taylor series describing the

trend dynamics function of a significant indicator.

The prognosis of complications of pregnancy is the

likely achievement of an undesirable state of health,

characterized by a set of indicators, for a certain

period of time. It is obvious that improving the

accuracy of the predict, if an undesirable trend of

significant indicators is detected, it is necessary to

reduce the time between the intervals of evaluating

the indicators of the current state. It will allow us to

estimate discrete values of trend dynamics and

derivatives of the Taylor series with greater accuracy.

When solving the problem under consideration, of

course, we are talking about a short-term predict for

several days, a maximum of a week. As the predict

time increases, the probability of reaching the

threshold values of the indicators will decrease.

2.5 Clinical Approbation of

Experimental Sample of the

Developed System

For experimental testing, a measuring channel was

selected that collects data on the dynamics of

biochemical parameters of urine. There are many

portable biochemical analyzers on the market that

allow you to conduct a general urine analysis at home.

For testing and subsequent inclusion in the hardware

and software complex, a portable analyzer was

selected that allows assessing the patient's health

status based on a set of 11 indicators:

1) glucose (GLU);

2) bilirubin (BIL);

3) relative density (SG);

4) pH;

5) ketone bodies (KET);

6) hidden blood (BLD);

7) protein (PRO);

8) urobilinogen (URO);

9) nitrites (NIT);

10) leukocytes (LEU);

11) ascorbic acid (VC).

To study the effectiveness of the device, as well

as to assess the accuracy of the results obtained (in

comparison with laboratory analysis) and the

feasibility of including the device in a remote

monitoring system, daily urine tests of a healthy

person were conducted for a month. Figure 3 shows a

summary graph of changes in the studied part of

indicators during the month.

Figure 3: Changes in the biochemical parameters of urine.

Based on the summary data, it is possible to

identify some patterns in the patient's health state. For

example, it can be seen that the levels of indicators

such as urobilinogen (URO), ketones (KET), glucose

(GLU), ascorbic acid (VC) and nitrates (NIT)

remained close to zero throughout the study. At the

1 4 7 10 13 16 19 22 25 28 31

Indicators value

Analysis day

NIT

URO

BLD

BIL

LEU

RMHM 2022 - Special Session on Remote Management and Health Monitoring

312

same time, the graph shows a jump in indicators such

as latent blood (BLD), protein (PRO), relative urine

density (SG) and urine pH. Outliers are observed for

five days, which corresponds to the period of critical

days in the subject. After the end of this period, the

indicators return to normal limits until the end of the

study. There is also a one-day outlier in the number

of white blood cells (LEU), which corresponds to the

recovery period after the introduction of the tested

vaccine against COVID-19 a day earlier.

In order to understand the degree of accuracy of a

separate study, a urine analysis of the subject was

conducted in parallel in the laboratory. Comparative

data of the analysis are given in Table 2.

Table 2: Comparative analysis of biochemical parameters

of urine.

Urine indicators Data from the

portable analyzer

Data from the

laboratory

analyzer

Urobilinogen <16 mkmol/l 10.7 mkmol/l

Hidden blood Negative Negative

Bilirubin Negative Negative

Ketone bodies 0 mmol/l 0.35 mmol/l

Leukocytes 0 1

Glucose Negative Negative

Protein Negative Negative

pH 5 4.9

Nitrites Negative Negative

Relative density 1.020 1.012

Ascorbic acid Negative Negative

Comparison of the results obtained using a

portable analyzer and a stationary analyzer in the

laboratory service allows us to identify minor

differences in three indicators: urobilinogen,

leukocytes and ketones. However, the differences in

them are insignificant and do not affect the overall

interpretation of the analysis results. Therefore,

diagnostics with the help of the analyzer under study

provides accuracy comparable to laboratory analysis.

3 CONCLUSIONS

The problem of remote monitoring of people's health

has become especially actual at the present time due

to many factors, including the spread of dangerous

viral diseases. Especially the changed living

conditions and the provision of medical care affected

pregnant women, greatly increasing the mortality rate

among the latter. The result of the study is a

generalized structure of the system that will allow

monitoring the condition of a pregnant woman

remotely, without reducing the quality of observation

and medical care using instrumental research

methods and an automated questionnaire. The

development of an experimental sample of a remote

monitoring system using certified portable devices

and medical systems has been carried out. Clinical

testing of measuring channels of the remote

monitoring system was carried out, its effectiveness

in remote monitoring conditions was proved. The

results obtained allow us to conclude that in the

conditions of isolation, self-isolation of a pregnant

woman, remote monitoring of a pregnant women's

health state and prediction of pregnancy

complications can solve the problem of monitoring

the health status of a pregnant woman and avoid

pregnancy complications. Certainly, such monitoring

and monitoring of a pregnant women's health state is

inferior in effectiveness if the patient were observed

in a clinic. There is no other alternative outside of

clinical conditions, and remote monitoring

technology should be further developed in the

direction of improving the quality of predicting

complications. The results of the study allow us to

summarize the experience of developing and using

remote monitoring systems for further development

of the technology.

REFERENCES

Villar, J., Ariff, S., Gunier, R. B., Thiruvengadam, R.,

Rauch, S., Kholin, A., ... & Papageorghiou, A. T.

(2021). Maternal and neonatal morbidity and mortality

among pregnant women with and without COVID-19

infection: the INTERCOVID multinational cohort

study. JAMA pediatrics.

Yap, M., Debenham, L., Kew, T., Chatterjee, S. R., Allotey,

J., Stallings, E., ... & Thangaratinam, S. (2020). Clinical

manifestations, prevalence, risk factors, outcomes,

transmission, diagnosis and treatment of COVID-19 in

pregnancy and postpartum: a living systematic review

protocol. BMJ open, 10(12), e041868.

Ryu, D., Kim, D. H., Price, J. T., Lee, J. Y., Chung, H. U.,

Allen, E., ... & Xu, S. (2021). Comprehensive

pregnancy monitoring with a network of wireless, soft,

and flexible sensors in high-and low-resource health

settings. Proceedings of the National Academy of

Sciences, 118(20).

Hema, L. K., & Anil, A. (2020, December). Pregnant

Women Health Monitoring System Using Embedded

System. In IOP Conference Series: Materials Science

and Engineering (Vol. 993, No. 1, p. 012078). IOP

Publishing.

A System for Remote Monitoring of Pregnant Women’s Health State and Pregnancy Complications Prediction

313

Korneeva, I. P. (2021, January). Method and System for

Estimation of Total Protein Concentration in an Urine

Sample for Early Diagnosis of Pregnancy

Complications. In 2021 IEEE Conference of Russian

Young Researchers in Electrical and Electronic

Engineering (ElConRus) (pp. 1769-1772). IEEE.

Semenova, E. A., & Timokhov, G. V. (2020, January).

Remote Health Monitoring System for a Patient with

Arterial Hypertension and Cardiac Arrhythmias. In

2020 IEEE Conference of Russian Young Researchers

in Electrical and Electronic Engineering (EIConRus)

(pp. 1578-1580). IEEE.

Kramar, K., & Semenova, E. A. (2021, January).

Automated Questionnaire to Assess the Current Health

State of a Pregnant Woman. In 2021 IEEE Conference

of Russian Young Researchers in Electrical and

Electronic Engineering (ElConRus) (pp. 1777-1780).

IEEE.

Schmidt, K., Aumann, I., Hollander, I., Damm, K., & von

der Schulenburg, J. M. G. (2015). Applying the

Analytic Hierarchy Process in healthcare research: A

systematic literature review and evaluation of reporting.

BMC medical informatics and decision making, 15(1),

1-27.

Yuldashev, Z. M., & Anisimov, A. A. (2017). A system for

remote-controlled intelligent monitoring of the health

status in humans. Biomedical Engineering, 51(1), 61-

65.

Mabikwa, O. V., Greenwood, D. C., Baxter, P. D., &

Fleming, S. J. (2017). Assessing the reporting of

categorised quantitative variables in observational

epidemiological studies. BMC health services research,

17(1), 1-8.

RMHM 2022 - Special Session on Remote Management and Health Monitoring

314