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Procedia Computer Science 00 (2019) 000–000
Procedia Computer Science 00 (2019) 000–000
ScienceDirect
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Procedia Computer Science 152 (2019) 267–273
International Conference on Pervasive Computing Advances and Applications – PerCAA 2019
International Conference on Pervasive Computing Advances and Applications – PerCAA 2019
Blood Pressure Monitoring System using Wireless technologies
Blood Pressure Monitoring System using Wireless technologies
Bharat Singha*
, Shabana Uroojbb, Sakshi Mishracc, Surojeet Haldardd
a*
Bharat Singh , Shabana Urooj , Sakshi Mishra , Surojeet Haldar
a,c,d
a,c,d
Bharatividyapeeth College of Engineering,New Delhi,110063,India
b
Gautam Buddha
University,Greter
Noida,201308,India
Bharatividyapeeth
College
of Engineering,New
Delhi,110063,India
b
Gautam Buddha University,Greter Noida,201308,India
Abstract
Abstract
This paper presents a simple solution for monitoring blood pressure in an economic and user-friendly method. Combining the
This
paper
a simple
for monitoring
blood pressure
in an economic
user-friendly
method. Combining
the
concepts
of presents
Internet of
Thingssolution
with an Arduino
microcontroller
and a pressure
sensor aand
Blood
Pressure Monitoring
System using
concepts
of Internet of Things
with an The
Arduino
microcontroller
a pressure
sensor
a Bloodpeople
Pressure
System
using
Wireless Technologies
are developed.
project
aims to setup and
a network
so that
concerned
can Monitoring
remotely access
patient’s
Wireless
Technologies
areBluetooth
developed.and
TheWi-Fi
project
aims to setup
a network
so that
concerned
people
remotely
patient’s
blood pressure
readings.
technology
are used
to access
results
on hand
heldcan
devices
likeaccess
mobiles,
tabs,
blood pressure
Bluetooth
and Wi-Fi
technology
are used
access results
on hand
held devices
like
tabs,
laptops
etc. Thereadings.
project also
incorporates
a prediction
algorithm
viatoMATLAB
software
program.
Readings
canmobiles,
be recorded
laptops
The project
also into
incorporates
a prediction
algorithm
via MATLAB
Readings
canforbetherecorded
overtimeetc.
manually
and when
the program
such a data
log is passed,
it predictssoftware
possible program.
blood pressure
values
patient
overtime
manually
andmedical
when into
the program
such aof
data
log is passed, it predicts possible blood pressure values for the patient
and
as well
as suggest
assistance
like dosage
medicines
and as well as suggest medical assistance like dosage of medicines
© 2019 The Authors. Published by Elsevier Ltd.
© 2019 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
© 2019
The
Authors.
Published
by Elsevier
Ltd.
This
is an
open
access
article under
BY-NC-ND
license
Peer-review
under
responsibility
of the
the CC
scientific
committee
of (https://creativecommons.org/licenses/by-nc-nd/4.0/)
the International Conference on Pervasive Computing Advances
This
is
an
open
access
article
under
the
CC
BY-NC-ND
license
(https://creativecommons.org/licenses/by-nc-nd/4.0/)
and Applications – PerCAA 2019.
Keywords: Drug Delivery System; Fuzzy Inference System; Mean Arterial Blood Pressure; Sodium Nitroprusside; Maximum a posteriori
estimators
Keywords: Drug Delivery System; Fuzzy Inference System; Mean Arterial Blood Pressure; Sodium Nitroprusside; Maximum a posteriori
estimators
1. Introduction
1. Introduction
In today’s world scenario most people with hectic schedules or suffering through immense stress often take their
In today’s
worldwhereas
scenariosome
mostdo
people
withhave
hectic
through
immense
stressissues
ofteneventually
take their
health
for granted,
not even
theschedules
facilities or
forsuffering
regular health
checkups.
These
health for
granted,that
whereas
some
do not
regular health
issues eventually
buildup
diseases
can turn
critical
or even
even have
fatal.the
Thefacilities
current for
generation
has to checkups.
live in an These
environment
which has
buildup
diseases stressful
that can turn
critical
even fatal.For
Theancurrent
generation
hasreported
to live inthat
an noise
environment
has
some
physically
effects
over or
individuals.
example
it has been
pollutionwhich
in urban
some
physically
stressful
individuals.
For an
example ithike
has been
reported
thatinnoise
urban
cities due
to traffic
or loudeffects
soundsover
from
speakers cause
a significant
in blood
pressure
evenpollution
a healthyinperson.
cities due
to traffichave
or loud
from
speakers
cause blood
a significant
hike
in blood [1]-[6].
pressure in even a healthy person.
Several
reseaches
beensounds
made in
field
of automatic
pressure
monitoring
Several
reseaches
have been
of automatic
blood
pressure In
monitoring
[1]-[6]. (BP) reading, the systolic
Millimeter
of mercury
or made
mmHginisfield
a manometric
unit
of pressure.
a blood pressure
Millimeter
mercury
or mmHg
is a manometric
unit
In ventricular
a blood pressure
(BP) reading,
the systole)
systolic
pressure
is theof
pressure
exerted
by blood
on the arteries
at of
thepressure.
time when
contraction
(also called
pressure is the pressure exerted by blood on the arteries at the time when ventricular contraction (also called systole)
occurs.
occurs.
* Bharat Singh. Tel.: +919015684701; fax: +0-000-000-0000 .
* E-mail
Bharat Singh.
Tel.: +919015684701;
fax: +0-000-000-0000 .
address:
singh.bharat10@gmail.com
E-mail address: singh.bharat10@gmail.com
1877-0509 © 2019 The Authors. Published by Elsevier Ltd.
This
is an open
access
under
the CC BY-NC-ND
license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
1877-0509
© 2019
Thearticle
Authors.
Published
by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
1877-0509 © 2019 The Authors. Published by Elsevier Ltd.
This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)
Peer-review under responsibility of the scientific committee of the International Conference on Pervasive Computing Advances
and Applications – PerCAA 2019.
10.1016/j.procs.2019.05.017
Bharat Singh et al. / Procedia Computer Science 152 (2019) 267–273
Bharat Singh / Procedia Computer Science 00 (2019) 000–000
268
2
Diastolic pressure is the pressure reading between two consecutive heartbeats. For an adult a normal resting blood
pressure measurements are 120mmHg for systolic and 80mmHg for diastolic, also abbreviated as 120/80 mmHg.
Irregular BP categories into two medical conditions namely hypertension and hypotension. Hypertension is when the
blood pressure in the arteries is persistently raised above 130/90 or 140/90 mmHg. Hypotension is low blood
pressure, mainly in the arteries of the circulation system (below 90/60mmHg) [7]. BP measurement is divided into
invasive blood pressure measurement and non-invasive blood pressure measurement. The project is based upon noninvasive blood pressure measurement [8].
There is a significant increase in cardio vascular diseases (CVD) due to hypertension. UN Sustainable
Development Goals draws spotlight to the necessity of controlling high rates of hypertension so that a target of
reducing non-communicable diseases by 1/3rd can be achieved by 2030. According to estimations about 400500,000 premature deaths can be prevent by better hypertension control [9].
Patients throughout world could be at a great benefit if they have an economical access to this real-time BP
monitoring system which has a user-friendly interface, such that anyone can learn how to operate. The project offers
a compact hardware system which is easily portable hence travel friendly. Wireless communication through Wi-Fi
and Bluetooth, gives us the ability to overcome geographical, cultural and linguistic barriers so that patients can
instantly share their BP readings with their doctors. Practitioners can recognize any irregularities by simply referring
the chart. The Blood Pressure Monitoring System using Wireless Technologies (BMPS) makes home-monitoring of
patients’ BP easier and improves the doctor-patient relationship. The system offers regular online monitoring for a
patient that proposes more enhanced diagnosis as well as improvement in efficiency and quality of administration
even during the absence of the doctor.
2. Components and Technology Used
There are multiple modules used in this system that serve their respective purpose. The following text has a small
description of each module.
2.1. Pressure Sensor: BMP180
BMP180 is a barometric pressure sensor with altitude and temperature sensor. The BMP180 sensor is built upon
the piezo-resistive technology for EMC robustness, high precision with linearity and also for long term stability [10].
Fig. 1. ESP8266-12E based Node MCU
Fig. 2. ESP8266-12E based Node MCU
The BMP180 comprises of a piezo-resistive sensor, control unit by E2PROM, an analog to digital converter and a
serial I2C interface. Sensor BMP180 conveys the uncompensated data of temperature and pressure. Microcontroller
directs a start sequence to initiate a pressure or temperature calculation. After translating time, the outcome value
(pressure or temperature respectively) is extracted via the I2C interface. For computing temperature in °C and
pressure in hPA, the calibrated data obtained initially must be utilized. [11]
2.2. Node-MCU With Wi-Fi Technology
A Wi-Fi wireless network works via radio waves, just the way mobile phones, TV sets and radios do.
Communication across a wireless network is majorly like to the two-way communication. The data is converted into
a radio signal by a computer's wireless adapter and then it gets transmitted by an antenna. A wireless router collects
Bharat Singh et al. / Procedia Computer Science 152 (2019) 267–273
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the signal and decodes it. The router transmits the data via a channel to the Internet by means of a physical and
established, wired ethernet connection. The procedure also functions in inverse, since the router can receive the
information from the Internet, then convert it into a radio signal and transmit it to the wireless adapter of the
computer. The NodeMCU module is an open source Internet of Things based platform. It is fitted with a firmware
which works on the ESP8266 Wi-Fi SoC from Espressif Systems.
2.3. Bluetooth Technology With HC-05 Module
Bluetooth is derived from the Master and Slave model. Its network architecture called the Piconet can allow
connection of up to 7 devices to the master. The master equipment can coordinate communication all over the
piconet, send and receive data from its slave. Bluetooth can exceed the 100 meter range.
Fig.3.HC-05 Bluetooth Module
Fig. 4. L293D dual motor driver H bridge
module board
The HC-05 is a Bluetooth SPP (Serial Port Protocol) module. By default the HC-05 module is set as slave. Supply
voltage to the module can be from3.3V to 5V.Pins in the module are enable key, Vcc, ground, TX(transmitter),
RX(Receiver) and state.
2.4. Internet Of Things
The Internet of Things (IoT) is the web of physical gadgets, home appliances, vehicles, and other embedded
devices with electronic components, firmware, measuring devices, actuators, and connectivity which allows all these
objects to connect and exchange information [11]. Each object is exclusively distinguishable via its embedded
computing system but it also has the ability to inter-operate through the prevailing Internet setup. [6] When sensors
and actuators are augmented with IoT, the technology develops an instance of the more general class of cyberphysical systems, which also incorporates technologies such as smart grids, virtual power plants, smart homes,
intelligent transportation and smart cities.
2.5. L293d Dual Motor Driver H Bridge Module Board
It uses the popular l293d motor driver IC. It drives 2 dc motors in both the directions.
2.6. KPM27H Mini Air Pump Motor
This is an air pump motor. It operates on 12 VDC nominal and Current of 300 mA. Maximum pressure that this
can exert by pumping air is 350 mm-Hg
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Fig. 5. KPM27H Mini Air Pump Motor
Fig. 6. Arduino Uno
2.7. Arduino Uno With ATmega328P Microcontroller
Build on the ATmega328P IC the Arduino Uno is a microcontroller board. Its pin configuration is that it has 14
digital output or input pins out of which PWM outputs can be produced by 6 pins. In addition to them there are 6
analog inputs, This microcontroller board can be programmed with the Arduino Software (IDE).
3. Wireless Blood Pressure Monitoring System Description
The goal of the project is to propose a system for flexible management structure allowing a network having easy
integration of heterogeneous sensors. The purpose of designing the system is to send BP readings quickly. Being
economical and portable it can be used at majority of places.
The traditional method of BP monitoring consists of readings being taken by a practitioner, which are then
recorded onto a paper. The paper then serves its purpose to help administer the BP record of the patient. Air is
pumped and released manually by a bulb up to a limit. A stethoscope is needed to monitor the pulse to guess the
expected blood flow from the artery. This requires skill and knowledge. The project eliminates the need of any
manual assistance by making pressure sensing, air pumping and release automatic, as well as no need of prior
knowledge for proper functioning of the system is required. BPMS eliminates the requirement of any person to
supervise the patient and the system. [14].
3.1. Architecture
The flowchart shown in fig 7 represents interconnections of components in the wireless blood pressure
monitoring system Similar to a mercury sphygmomanometer the BPMS consists of an inflatable cuff. A KPM27H
Mini Air Pump is required to inflate the cuff via a pipe. The valve guides the air flow between the air pump and the
cuff. The H-bridge motor driver controls and commands the valve as well as the air pump. The pressure sensor
BMP180 is sealed inside an air tight case. NodeMCU serves as a microcontroller for receiving and transferring
signals with other parts of the system. The instructions and algorithms are fed to NodeMCU via Arduino IDE 1.8.5.
Fig. 7. Block Diagram of BMPS
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3.2. Working
The cuff is wrapped around the arm (preferably left) at the same level near the heart. When the start button is
pushed by the user, the command gets recognised and the air pump inflates the cuff up to 180mmHg of pressure
which is simultaneously read by the pressure sensor. The valve is signalled to close the air pipe pathway so that the
air pressure remains in the cuff. When air cuff is fully inflated, a very minute volume of blood movement occurs
inside the artery. The blood flow exerts a pressure on to the arterial wall and establishes noticeable vibrations in the
arterial wall. When the cuff pressure drops such that it is under the patient's diastolic pressure, blood flows easily
through the artery with the usual pulses, minus any vibration being established in the wall. The vibrations are
conveyed from the arterial wall, through the air within the cuff, into a casing which seals the pressure sensor
BMP180 inside. The vibrations cause change in pressure in the air column via the air tube and then within the casing
which the BMP180 realizes. The pressure sensor converts the measurements into electrical signal. The value of
pressure is calibrated to units of mmHg by the sensor itself. This value is the systolic BP. This measurement is send
to the NodeMCU [15].
For display of BP value wireless technology is employed. HC-05 Bluetooth module is utilised to connect to other
Bluetooth compatible devices. An app Bluetooth Terminal HC-05 is used here for the purpose of connection. Once
the value gets uploaded to the microcontroller it sends tha data by serial communication through the Bluetooth
module, to the gadget (like mobile, tablet, computer etc.) which displays the BP readings.
Another wireless communication method Wi-Fi is also employed. NodeMCU comes with an inbuilt ESP826612E chip. The NodeMCU can be connected to an existing wireless network or it can also serve as a hotspot and
provide a network connection on its own. In both cases the Wi-Fi chip exhibits a characteristic IP address. Devices
connected to the same networks as the NodeMCU is connected to or connected to the network connection setup by
the ESP8266-12E itself can access the IP address. The network connection is secured by WAP protocol. The IP
address is entered into the address bar of any web browser. Once the connection is set between the device and
NodeMCU a HTML webpage gets loaded which displays the patient’s readings.
BP readings are simultaneously noted in an excel sheet. The MATLAB program offers Neural Network Training
application which has been used here to employ the prediction algorithm. A patient’s medicinal dosages are
recorded manually in an excel sheet with respect to time. These dosage readings are passed as input to the neural
network configuration. The predicted output shall be the expected values of BP. To start of with the program, the
appropriate number of neurons are set for better accuracy and trained until desired precision is obtained.
4. Observations
Multiple trials on various people have derived a more accurate system. When the system measured the BP of
those candidates who didn’t exhibit any blood pressure related medical problems or any CVDs, the readings ranged
from 110mmHg to 135mmHg for systolic. When measurements were done on a patient of hypertension, the readings
ranged from 150-160mmHg. Android devices installed with HC-05 bluetooth terminal application displayed the
readings. Mobile devices with Wi-Fi connection as mentioned also displayed the readings when the IP addresses
were accessed by the user.
Fig. 8. Webpage display on Wi-Fi connected device
MATLAB prediction program when ran for a patient of hypertension with respective medicinal dosages for each BP
value following results were obtained. Fig 9 shows the neural network training results and in fig 10 predicted blood
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pressure are shown and accordingly drug dose can be evaluated.
140
120
BP(mmhg)
100
80
60
40
20
0
Fig. 9. Neural Network Trainer Result
0
5
10
15
Time(sec)
20
25
30
Fig. 10. Graphical plot of forecasted BP readings
The Arduino IDE serial plotter exhibits the graph which shows the variation in the pressure of blood in the artery
of the candidate upon whom the experiment was conducted
Fig. 11.Arduino Serial Monitor displaying Result
5. Conclusion
The motive of making the project economic is achieved as the project costs less than thousand Rupees. Only one
command to start is required by the system which is processed by pressing a button, hence operation is easy.
Absence of any wires or bulky components makes is compact, flexible and travel friendly. Connecting to the
network a doctor can administer the patient’s data from a distance successfully. A memory component can be
incorporated into the system such that it holds the data log. This may help in saving data electronically and
automatically rather than recording it manually. Modern day health apps can calibrate with the system such that they
can also monitor and advice medical assistance. The prediction program can be fed to medical machines which can
use this data to automatically release appropriate medicinal dosage invasively in cases of emergency. This can
reduce the time needed by practitioners to save lives. Extreme BP readings if noted by the system then emergency
contacts are informed immediately.
References
[1]
H. Tuzel (1974), “Sodium nitroprusside: a review of its clinical effectiveness as a hypotensive agent,” The Journal of Clinical
Pharmacology, 14(10):. 494–502.
[2]
P. Engeser, R. Roeßle, and J. Pill, (1982), “E_ects of long term infusion of sodium nitroprusside on iron and thiocyanate in rabbits,”
Archives of Toxicology, 51(4): 323–328.
[3]
K. Chakravarty and D. Dalal, (2017) “An analytical study of drug release to biological tissues through endocytosis,” International
Journal of Dynamics and Control. 1–12.
[4]
Koyel Chakravarty and D C Dalal. (2016) “A two-layer mathematical modelling of drug delivery to biological tissues,” Journal of
Physics: Conference Series 759(1): 12–23.
[5]
L. C. Sheppard.(1980), “Computer control of the infusion of vasoactive drugs,” Annals of biomedical engineering 8( 4-6) : 431–444.
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[6]
Bharat Singh and Shabana Urooj(2018) “Intravenous Drug Delivery System for Blood Pressure Patient Based on Adaptive Parameter
Estimation” International Journal of Natural Computing Research 7( 3): 42-53.
[7]
[8]
https://en.wikipedia.org/wiki/Hypotension_
M. Huang, J. Huang, J. You and G. Jong, "The Wireless Sensor Network for Home-Care System Using ZigBee," Third International
Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP 2007), Kaohsiung, 2007, pp. 643-646.
[9]
R. Gupta, D Xavier, (2018) “Hypertension: The most important non communicable disease risk factor in India,” India Heart
Journal70(4):565-572
[10] https://cdn-shop.adafruit.com/datasheets/BST-BMP180-DS000-09.pdf< accessed on April 11 ,2018>
[11] https://wiki.eprolabs.com/index.php?title=Pressure_Sensor-BMP_180<accessed on march 22, 2018
[12] Brown, Eric (13 September 2016) "Who Needs the Internet of Things?" Linux.com.
[13] F.Mattern , C. Floerkemeier. (2010) From the Internet of Computers to the Internet of Things. In: Sachs K., Petrov I., Guerrero P. (eds)
From Active Data Management to Event-Based Systems and More. Lecture Notes in Computer Science, vol 6462. Springer, Berlin,
Heidelberg
[14] Instant Notification System In Heterogeneous Sensor Network With Deployment Of XMPP Protocol - 2013 International Conference
on Cloud & Ubiquitous Computing & Emerging Technologies
[15] YV Varshney , and AK Sharma (2013) "Design & simulation of Zigbee transceiver system using Matlab." Network 255.65K: 13161319