=Paper= {{Paper |id=Vol-2850/paper3 |storemode=property |title=Architecture for edge devices for diagnostics of students' physical condition |pdfUrl=https://ceur-ws.org/Vol-2850/paper3.pdf |volume=Vol-2850 |authors=Tetiana M. Nikitchuk,Tetiana A. Vakaliuk,Oksana A. Chernysh,Oksana L. Korenivska,Liudmyla A. Martseva,Viacheslav V. Osadchyi |dblpUrl=https://dblp.org/rec/conf/doors/NikitchukVCKMO21 }} ==Architecture for edge devices for diagnostics of students' physical condition== https://ceur-ws.org/Vol-2850/paper3.pdf
Architecture for edge devices for diagnostics of
students’ physical condition
Tetiana M. Nikitchuka , Tetiana A. Vakaliuka,b , Oksana A. Chernysha ,
Oksana L. Korenivskaa , Liudmyla A. Martsevaa and Viacheslav V. Osadchyic
a
  Zhytomyr Polytechnic State University, 103 Chudnivsyka Str., Zhytomyr, 10005, Ukraine
b
  Institute of Information Technologies and Learning Tools of the NAES of Ukraine, 9 M. Berlynskoho Str., Kyiv, 04060,
Ukraine
c
  Bogdan Khmelnitsky Melitopol State Pedagogical University, 20 Hetmanska Str., Melitopol, 72300, Ukraine


                                         Abstract
                                         The article investigates the possibility of technical realization of hardware complex. It presupposes
                                         the use of sensors of registration of a photoplethysmographic curve, which describes a pulse wave
                                         and defines the parameters of students’ cardiovascular system functional state. The method of pho-
                                         toplethysmography allows the use of non-contact sensors. Therefore, there is no artery compression,
                                         which eliminates circulatory disorders and allows the use of calculations to determine the saturation of
                                         oxygen by the pulse wave. It is recommended to use several optocouplers connected in series, parallel
                                         or parallel-series in a chain, with control of their mode of operation from the intensity of the received
                                         pulse wave signal depending on human body constitution. The edge device hardware is a part of the
                                         IoT system, which also includes another edge device, which instantly transmits data to the database on
                                         the edge server for the data further processing and storage.

                                         Keywords
                                         pulse wave, saturation, edge device, sensor, biotechnical system, photoplethysmography,
                                         photoplethysmograph




1. Introduction
2020 is the year of the COVID-19 pandemic [1], which forced people to change their attitude
to health. In the period of morbidity, when the number of the infected is constantly increasing


QuaInT 2021: Workshop on the Quantum Information Technologies, April 11, 2021, Zhytomyr, Ukraine
doors 2021: Edge Computing Workshop, April 11, 2021, Zhytomyr, Ukraine
" tnikitchuk@ukr.net (T.M. Nikitchuk); tetianavakaliuk@gmail.com (T.A. Vakaliuk); chernyshoxana@gmail.com
(O.A. Chernysh); o.l.korenivska@gmail.com (Oksana L. Korenivska); l.a.martseva@gmail.com (L.A. Martseva);
poliform55@gmail.com (V.V. Osadchyi)
~ https://ztu.edu.ua/ua/structure/faculties/fikt/krt.php (T.M. Nikitchuk);
https://sites.google.com/view/neota/profile-vakaliuk-t (T.A. Vakaliuk); https://ztu.edu.ua/ua/structure/pv/ (O.A.
Chernysh); https://ztu.edu.ua/ua/structure/faculties/fikt/teachers_krt.php (Oksana L. Korenivska);
https://ztu.edu.ua/ua/structure/faculties/fikt/teachers_kikm.php (L.A. Martseva); http://osadchyi.mdpu.org.ua
(V.V. Osadchyi)
 0000-0002-9068-931X (T.M. Nikitchuk); 0000-0001-6825-4697 (T.A. Vakaliuk); 0000-0002-2010-200X (O.A.
Chernysh); 0000-0002-3735-7690 (Oksana L. Korenivska); 0000-0001-5037-6565 (L.A. Martseva);
0000-0001-5659-4774 (V.V. Osadchyi)
                                       © 2021 Copyright for this paper by its authors.
                                       Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
    CEUR
    Workshop
    Proceedings
                  http://ceur-ws.org
                  ISSN 1613-0073       CEUR Workshop Proceedings (CEUR-WS.org)
Figure 1: The number of people infected with COVID-19 at the end of 2020


exponentially (figure 1), early detection of certain abnormalities in health is a precautionary
measure.
   One of the requirements to participate in any event as well as attend classes is a satisfactory
health condition. Therefore, in an educational institution, the problem of determining students’
state of health arises.
   Due to the COVID-19 outbreak, it has become impossibile to monitor the health condition
of a student body. Therefore, it is proposed to develop edge devices, the components of which
will be partially located in classrooms.
   The system screens and monitors the functional parameters of students’ cardiovascular sys-
tem and other organs for coronavirus symptoms, pre-existing and health condition. It displays
the result on the edge device screen, or transfers it server, or a mobile device.
   In the last decades of the last century – at the beginning of the current for the functional
diagnosis of the cardiovascular and respiratory systems and, to some extent, the functional
features of the circulatory system, pulse oximeters have become widespread. These are devices
designed to determine the relative saturation of blood hemoglobin with oxygen in the natural
conditions of human life and the dynamics of its performance of various functional tests [2, 3,
4].
   In the middle – the last quarter of the 20th century photooxyhemographs were widely used
to solve the problem mentioned above. Modern integrated pulse oximeters, in contrast, al-
low obtaining high-quality curves of peripheral arterial pulse due to periodic heart activity –
photoplethysmograms (PPG) [2, 5].
   The contour and form of photoplethysmograms greatly resembles the peripheral pulse curve
(sphygmogram) obtained with mechanical pressure sensors that convert the oscillations of the
wall of the pulsating artery into an electrical signal [2, 4, 5]. Therefore, pulse oximetry can



                                               46
be used as a source of primary biological information about heart rate and natural heart rate
variability [5].
  Edge devices are viewed as a complex automated system [6]. It combines memory hard-
ware (considered in the paper), data transmission and visualization unit, and the database. The
database contains students’ medical records, medical check-up data, and the data of patients’
health condition monitoring.

1.1. Theoretical background
Prior researches proves that the introduction of ICT in the field of health care greatly con-
tributes to health promotion and maintenance [7, 8, 9, 10, 11, 12, 13, 14]. Moreover, it impoves
the demographic situation, upgrades the quality and efficiency of health care. Furthermore, it
ensures the human rights to health care [7]. V. Avramenko, V. Kachmar and A. Khvyshchun
[7, 15, 16] have made a significant scientific and practical contribution to the introduction of
modern information technologies in the educational process as well as in health care institu-
tions work in Ukraine.
   A closer look to the literature on medical field informatization, however, reveals a number
of gaps and shortcomings. Although there are many studies, the research in the assessment
of medical information systems effectiveness remains limited. Nonetheless, there exists a con-
siderable body of literature on organizational and economic efficiency of industrial, corporate,
accounting and other types of information systems introduction in large enterprises, govern-
ment agencies, and in the tourism industry [7, 17, 18, 19, 20, 21].
   The study addresses several further questions on edge computing, which is a comparatively
new area of research [22]. However, it has been successfully established and described by
Najmul Hassan, Saira Gillani, Ejaz Ahmed, Ibrar Yaqoob and Muhammad Imran. The scientists
bring some information about the role of edge computing in the internet of things [23]. They
propose a layered model for the delivery of IoT services based on CloudEdge, as well as the
taxonomy of the Edge Environment based on IoT (see figure 2). Moreover, the researchers
provide a clear illustration of cloud computing complementary role in the IoT environment
(see figure 3) [23].
   A more comprehensive description can be found in the works of Inés Sittón-Candanedo
and Juan Manuel Corchado. The scientists consider the concept of Edge Computing, and the
possibility of Edge Computing integration. They suggest that it significantly contributes to
optimizing the processes that are usually performed in a cloud computing environment [24]. In
addition, the scientists successfully establish the relation between Edge and Cloud Computing
(figure 4) [24].
   Jun-Ho Huh and Yeong-Seok Seo present the framework, preconditions and discuss the ad-
vantages and disadvantages of edge calculations. The researchers describe how they function
and provide their structure hierarchically with the concepts of artificial intelligence [25]. More-
over, the scientists draw a comparison of the cloud and edge computing paradigm; propose a
three-tier edge computing architecture, and develop the design of an edge computing environ-
ment with AI support (see figure 5).
   The aim of this research is to develop the hardware of edge devices of pulse rapid diagnos-
tics of human body functional state. Its parameters enable to identify the early symptoms of



                                                47
Figure 2: Taxonomy of IoT-based Edge Environment [23]


COVID-19 and determine the functional state of cardiovascular system. The hardware serves
as a means of determining the parameters of human body functional state and can be installed
in the places of student’ study.


2. Results
The hardware complex is located in the classrooms and consists of 2 units:
   1. the unit for determining students’ health condition according to 4 parametres:
          • body temperature
          • saturation (oxygen saturation) of blood
          • heart rate (HR)
          • rapid diagnostics of cardiovascular system functional state
   2. indoor air quality monitoring unit.
   The article reviews the possibility of technical realization of hardware complex. It presup-
poses the use of sensors of registration of a photoplethysmographic curve, which describes a
pulse wave and defines the parameters of students’ cardiovascular system functional state.
   The method of photoplethysmography is designed to study the cardiovascular system of
biological objects in which the measurement of characteristics and parameters of blood circu-
lation (pulse curve, blood pressure, arterial oxygen saturation level, etc.), vascular reactions and
metabolic processes are performed by recording the fluxes intensity of electromagnetic radia-
tion in the optical range (from visible – 0.4 𝜇m to near-infrared – 1.5 𝜇m) after their interaction
with the tissues of a living organism [26].
   There are two types of photoplethysmographic methods: transmitted-light photoplethys-
mography and side-scattered photoplethysmography (figure 6).



                                                48
Figure 3: Illustration of Edge Cloud Computing Complimentary Role in IoT Environment [23]


   The on the lumen method allows to install the sensor on a finger or an earlobe, as the radiat-
ing unit should fully X-ray the area. Moreover, the receiver, which is located perpendicularly,
captures the light quantity that has passed through the finger. The on the reflection method
presupposes that the light quantity from the radiating unit falls on a certain part of the body.
In such a case, some of the light is absorbed, and some is reflected and enters the code receiver.
This method is more universal, as it is possible to place the sensor on any part of the body, if
full contact with him is provided [26, 27, 28].
   The basis of photopulse oximetry method lies in the measurement of light absorption of
a certain wavelength by blood hemoglobin. Hemoglobin serves as a filter, what is more, the
“color” and “thickness” of this natural filter can vary [27, 28]. The “color” of the filter depends
on the percentage of oxyhemoglobin. That is how pulse oximetry determines the level of blood
oxygenation.
   Changes in the “thickness” of the filter are affected by the pulsation of the arterioles: each
pulse wave increases the amount of blood in the arteries and arterioles. The doctor defines this
as a pulse rate, and the pulse oximeter considers that as a “thickening” of the filter. In such a
way, the pulse rate and amplitude of the pulse wave are measured.



                                                49
Figure 4: Edge and Cloud Computing [24]




Figure 5: A design of Edge Computing Environment Supported by AI [25]


  Therefore, the use of one measurement principle allows determining three diagnostic pa-
rameters: the levels of saturation of hemoglobin with oxygen, the pulse rate and its “volume”
amplitude. In addition, it enables further processing and analysis of pulse waves to determine
the functional state of cardiovascular system.




                                              50
Figure 6: Ways of Sensors Location for Blood Circulation Registration. a) on the lumen, b) on the
reflection




Figure 7: The Survey Plan of Information System Hardware


   The registration of photoplethysmographic signals [5] is performed using the scheme shown
in figure 7.
   The analog part of the hardware consists of an optical sensor unit, an amplifier, and mod-
ulating equipment. The other units belong to the digital part. Amplified signals coming from
the sensor unit, via USB-input are transmitted to the PC and the program window displays a
pre-processed photoplethysmographic signal.
   To transfer data from the microcontroller to the PC, USB port is used.
   The method of photoplethysmography allows the use of non-contact sensors. Therefore,
there is no artery compression, which eliminates circulatory disorders and allows the use of
calculations to determine the saturation of oxygen by the pulse wave. Taking into consider-
ation that the hardware of the signal recording system is required for further transmission,
processing and analysis of pulse waves, the method of finger photoplethysmography is insuf-




                                               51
Figure 8: The Survey Plan of BTS Pulsogram Hardware Based on the Parametres of the Photopulse
Oxygenation on the basis of PC


ficient in its practical use.
   On the one hand, the method is sufficient if the end phalanx of the finger or foot is X-rayed
on one side by ordinary incoherent light, which after side-scattering enters the photodetector;
however, on the other hand, this method is not appropriate to obtain sufficiently intense signals
from radial artery. However, it should be mentioned that the signal from radial artery is the
most informative for cardiovascular system diagnosis. Nonetheless, this signal also depends
on the human body constitution, its anthropometric parameters in particular. To consider this
and to make the study of pulse waves and cardiovascular system more reliable we recommend
controlling the intensity of infrared light depending on the human body constitution. The use
of one optocoupler is not enough for this due to the low power of the light quantity and the
depth of its penetration. It is recommended to use several optocouplers connected in series,
parallel or parallel-series in a chain, with control of their mode of operation from the intensity
of the received pulse wave signal depending on human body constitution (figure 8). Small
optocouplers design allows doing it on a small plane, which the sensor itself has.
   In the case of photopulse oxygenation, we are interested in the absorption of light quantity
by blood running through veins, arterial blood in particular. Thus, the aim of pulse oximetry
is to measure the level of saturation of hemoglobin in arterial blood with oxygen.
   Hemoglobin is the common name for blood proteins found in red blood cells. Oxyhemoglobin
is fully oxygenated hemoglobin, each molecule of which contains four oxygen molecules. De-
oxyhemoglobin is hemoglobin that does not contain any oxygen.
   The tissues through which both light quantity pass are a non-selective filter and evenly
attenuate the radiation of both LEDs. The degree of attenuation depends on tissues thickness,
skin pigment and other obstacles in the way of light. Hemoglobin, in contrast to tissues, is a
color filter, and the color of this filter is affected by the level of oxygen saturation of hemoglobin.
Deoxyhemoglobin has a dark cherry color. It intensively absorbs red light and weakly delays
infrared. Therefore, if to put blood that does not contain any oxygen under the red and infrared
light, the first one will be almost completely held, and the second one will be only slightly
weakened. Conversely, oxyhemoglobin scatters red light (therefore, it has a red color), but
intensely absorbs infrared radiation.
   Thus, the ratio of two light quantities under the photodetector depends on blood oxygen sat-



                                                  52
Figure 9: The Program Window




Figure 10: The Hardware and Software Complex Overview and the window with pulsegrams


uration level. According to these data, using a certain algorithm, the microprocessor calculates
the percentage of oxyhemoglobin in the blood.
   Therefore, using the unit of photoplethysmography and implying the methods of photo-
plethysmographic signal digital processing, we obtain the result as shown in figure 9.
   In order to read the pulse signal, it is possible to connect the sensor directly to the laptop,
previously pre-amplifying the signal. Moreover, it is also possible to implement a small model
in the MATLAB package [29, 30] for further analysis of pulsegrams. It should be noted that the
display of the pulse graph is in real time. What is more, data can be stored in the database. It
is rather convenient for keeping the records and dealing with statistics.
   Non-invasive methods of registration, analysis and evaluation of amplitude-time parameters
of pulse signals [31, 32, 33, 34, 35, 36] are viewed as a set of modern technical means and
mathematical methods of processing biosignals. Nowadays, they define the current trends



                                               53
in cardiovascular system as well as other systems diagnostics. Furthermore, determination
of additional values of saturation and body temperature is an important issue which is not
restricted to rapid students’ diagnostics only.


3. Conclusions
The paper proposes a device for recording pulse signals, which can record not only the heart
rate but also measure saturation, which significantly minimizes the design of the device.
   The edge device hardware is a part of the IoT system, which also includes another edge
device, which instantly transmits data to the database on the edge server for the data further
processing and storage. In addition, further detailed study of edge device data as a part of the
IoT System is needed. Furthermore, the development of a mobile application to display the
data is planned. This will allow you to monitor changes in the physiological parameters of the
student in real-time around the clock and/or record on the server and, if necessary, view them.


References
 [1] S. Semerikov, S. Chukharev, S. Sakhno, A. Striuk, V. Osadchyi, V. Solovieva, T. Vakaliuk,
     P. Nechypurenko, O. Bondarenko, H. Danylchuk, Our sustainable coronavirus future,
     volume 166, EDP Sciences, 2020. doi:10.1051/e3sconf/202016600001.
 [2] I. B. Isupov, R. S. Zatrudina, Electronic module for photoplethysmography and pulse
     oximetry, Natural Systems and Resources 8 (2018).
 [3] D. Rogatkin, Physical basis of optical oximetry, Medical Physic 2 (2012) 97–114.
 [4] S. Munir, A. Guilcher, T. Kamalesh, B. Clapp, S. Redwood, M. Marber, P. Chowienczyk,
     Peripheral augmentation index defines the relationship between central and peripheral
     pulse pressure, Hypertension 51 (2008) 112–118. doi:10.1161/HYPERTENSIONAHA.
     107.096016.
 [5] T. N. Nikitchuk, V. F. Manoilov, P. P. Martynchuk, Recording technique of photoplethys-
     mographic signals for study in the phase plane, in: 2012 22nd International Crimean
     Conference "Microwave Telecommunication Technology", 2012, pp. 981–982.
 [6] A. V. Ryabko, O. V. Zaika, R. P. Kukharchuk, T. A. Vakaliuk, Graph model of Fog Com-
     puting system, CEUR Workshop Proceedings (2021).
 [7] K. Kopnyak, Estimation of efficiency of medical information systems introduction, Econ-
     omy and organization of management 2 (2017) 109–119.
 [8] O. Gorna, T. Stanishevska, T. Kopulova, O. Yusupova, D. Horban, Research of the somatic
     health of student youth using information and communication technologies, E3S Web of
     Conferences 166 (2020). doi:10.1051/e3sconf/202016610034.
 [9] O. Klochko, V. Fedorets, O. Maliar, V. Hnatuyk, The use of digital models of hemodynamics
     for the development of the 21st century skills as a components of healthcare competence
     of the physical education teacher, E3S Web of Conferences 166 (2020). doi:10.1051/
     e3sconf/202016610033.
[10] O. Klochko, V. Fedorets, A. Uchitel, V. Hnatyuk, Methodological aspects of using aug-




                                              54
     mented reality for improvement of the health preserving competence of a physical edu-
     cation teacher, CEUR Workshop Proceedings 2731 (2020) 108–128.
[11] H. Meshko, O. Meshko, N. Drobyk, O. Mikheienko, Psycho-pedagogical training as a mean
     of forming the occupational stress resistance of future teachers, E3S Web of Conferences
     166 (2020). doi:10.1051/e3sconf/202016610023.
[12] Y. Nosenko, A. Sukhikh, The method for forming the health-saving component of basic
     school students’ digital competence, CEUR Workshop Proceedings 2393 (2019) 178–190.
[13] Y. Nosenko, A. Sukhikh, O. Dmytriienko, Organizational and pedagogical conditions of
     ict health-saving usage at school: Guidelines for teachers, CEUR Workshop Proceedings
     2732 (2020) 1069–1081.
[14] D. Shiyan, I. Ostapchuk, O. Lakomova, Geographical analysis of ecology-dependent
     diseases of kryvyi rih population in order to provide a sustainable development of
     the industrial regions, E3S Web of Conferences 166 (2020). doi:10.1051/e3sconf/
     202016601012.
[15] V. Kachmar, V. Avramenko, Directions of development of information technologies in
     medicine, Medicine of transport of Ukraine 3 (2011) 96–103.
[16] V. Kachmar, A. Khvyshchun, Electronic medical record of the patient. mutual compati-
     bility and standardization, Ukrainian Journal of Telemedicine and Medical Telematics 6
     (2008) 76–79.
[17] O. Hanchuk, O. Bondarenko, I. Varfolomyeyeva, O. Pakhomova, T. Lohvynenko, Couch-
     surfing as a virtual hospitality network and a type of sustainable youth tourism, E3S Web
     of Conferences 166 (2020). doi:10.1051/e3sconf/202016609005.
[18] A. Kiv, V. Soloviev, S. Semerikov, H. Danylchuk, L. Kibalnyk, A. Matviychuk, Experimental
     economics and machine learning for prediction of emergent economy dynamics, CEUR
     Workshop Proceedings 2422 (2019) 1–4.
[19] I. Lutsenko, E. Vihrova, E. Fomovskaya, O. Serdiuk, Development of the method for testing
     of efficiency criterion of models of simple target operations, Eastern-European Journal of
     Enterprise Technologies 2 (2016) 42–50. doi:10.15587/1729-4061.2016.66307.
[20] V. Soloviev, A. Belinskiy, Complex systems theory and crashes of cryptocurrency
     market, Communications in Computer and Information Science 1007 (2019) 276–297.
     doi:10.1007/978-3-030-13929-2_14.
[21] S. Zelinska, A. Azaryan, V. Azaryan, Investigation of opportunities of the practical ap-
     plication of the augmented reality technologies in the information and educative envi-
     ronment for mining engineers training in the higher education establishment, CEUR
     Workshop Proceedings 2257 (2018) 204–214. 1st International Workshop on Augmented
     Reality in Education, AREdu 2018 ; Conference Date: 2 October 2018.
[22] T. Lorido-Botran, M. K. Bhatti, ImpalaE: Towards an optimal policy for efficient resource
     management at the edge, CEUR Workshop Proceedings (2021).
[23] N. Hassan, S. Gillani, E. Ahmed, I. Yaqoob, M. .Imran, The role of edge computing in
     internet of things, IEEE Communications Magazine 56 (2018) 110–115. doi:10.1109/
     MCOM.2018.1700906.
[24] I. Candanedo, J. Corchado, An edge computing tutorial, Orient. J. Comp. Sci. and Technol.
     12 (2019). doi:10.13005/ojcst12.02.02.
[25] J. Huh, Y. Seo, Understanding edge computing: Engineering evolution with artificial in-



                                              55
     telligence, IEEE Access 7 (2019) 164229–164245. doi:10.1109/ACCESS.2019.2945338.
[26] V. Alekseev, A. Perminov, S. Yuran, Mutual arrangement of the source and receiver of the
     sensor radiation for photoplethysmography, Instruments and methods of measurements
     1 (2011).
[27] S. Pavlov, V. Kozhemyako, V. Petruk, P. Kolisnyk, Photoplethysmographic technologies
     of control of the cardiovascular system, UNIVERSUM-Vinnytsia, Vinnytsia, 2007.
[28] I. Shurygin, Respiration monitoring: pulse oximetry, capnography, oximetry, BINOM,
     Moscow, 2000.
[29] T. Nikitchuk, Devising an information system for the analysis of pulse signals, Eastern-
     European Journal of Enterprise Technologies 5 (2015) 19–23. URL: http://journals.uran.
     ua/eejet/article/view/51219. doi:10.15587/1729-4061.2015.51219.
[30] A. Leonenkov, Fuzzy modeling in MATLAB and fussy TECH, BHV-Petersburg, 2005.
[31] T. H. Nikitchuk, V. F. Manoylov, The technique of pulse signals processing in a phase
     plane, in: 2011 21st International Crimean Conference "Microwave Telecommunication
     Technology", 2011, pp. 1040–1041.
[32] L. Ayusheeva, V. Boronoev, I. Lebedintseva, I. Ledneva, Time parameters of the pulse
     wave in the diagnostics of human diseases according to the tradition of tibetan medicine,
     Biomedical Radioelectronics 3 (2009) 17–23.
[33] V. Mosiychuk, Multisignal digital registration and processing of pulse wave parameters,
     Ph.D. thesis, Nat. tech. University of Ukraine ’Kyiv Polytechnic Institute’, Kyiv, 2011.
[34] T. Kozlovskaya, Optical-electronic device for diagnosing the state of peripheral circula-
     tion with high reliability, Ph.D. thesis, Vinnytsia National Technical University, Vinnytsia,
     2012.
[35] O. Voloshin, V. Oleinik, S. Kulish, A. O. Sami, Ekg method for diagnostics of human
     functional state on the basis of fractal analysis and wavelet transform, Radioelectronic
     and Computersystems 4 (2010) 29–34.
[36] L. Fainzilberg, New opportunities of phasegraphy in medical practice, Science and Inno-
     vation 13 (2017) 37–50.




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