This document describes a smart healthcare system that uses IoT devices to remotely monitor patients' ECG signals. The system uses an ECG sensor connected to a microcontroller that transmits real-time ECG data to a server via WiFi. Doctors can access this data from anywhere to diagnose patients. The system aims to make healthcare more accessible for people in rural areas by allowing remote monitoring and diagnosis without visiting clinics. The document outlines the hardware, software, data transmission process, and how ECG data can be analyzed to diagnose various heart conditions.

1. Acquisition and Analysis of ECG
Signal
Presented by-
THUNDERBOLTZ
•SOURADEEP MULLICK
•SAYAN SARKAR
•SPANDAN PAUL

2. BUSINESS PROBLEM
ISSUES
• Conventional
ECG,PPG,PCG tests
need to be visited in
diagnostic centres every
time.
• Inconveniences for the
persons who live in
undeveloped rural area.
• Problem for the old
persons who need ECG
routine checkups
IMPACT
• This project is mainly based on
ECG Monitoring system. But
we can apply this project in
different diagnosing systems
using different sensor
• Now a patient need not visit a
diagnostic center for different
health tests like ECG,PCG,PPG
• With the help of an app the
patient himself can analyse
his/her problems more or less
and it will give him the
information of basic treatment.
SOLUTION
• Smart Health Care System
is required by which a
patient sitting at home, can
be diagnosed by a doctor
who is anywhere in the
world.
•Real time data monitoring.
•Patient Health data can be
visualized and analyzed
from anywhere in the world.
THEME
IoT
DURATION
450 hrs.
INDUSTRY
Healthcare

3. WHAT IS IOT ?
The Internet of things (IoT) is the network of
physical devices, vehicles, home appliances, and
other items embedded with electronics, software,
sensors, actuators, and connectivity which enables
these things to connect, collect and exchange data

4. Health Care IoT System
 IoT vision, enable a smart hospital system
(SHS).
 Internet connected devices have
been introduced to patients in various
forms .
 This creates an opening for smarter devices
to deliver more valuable data, lessening
the need for direct patient physician
interaction.
 IOT is coupled with home medication dispe
nsers to automatically upload data to the
cloud when medication isn't taken or any
other indicators for which the care team
should be alerted.

6. WHY HEALTHCARE IoT ?

7. ISSUE
 Conventional ECG tests need to be visited in
diagnostic centres every time. Even if this test can be
done in home, yet continuous monitoring of heart rate
& rhythm is impossible
 Again the person has to move to the hospital or clinics
to show the report to the doctor. It can be possible if
the doctor’s clinic is in the near locality. But what if the
patient wants to be diagnosed by a doctor who is far
away from him, for example in a different city or
country?
 It is also difficult for a person who belongs to an
undeveloped rural area having lack of treatment
opportunities, to be diagnosed by a doctor belongs to
far away city.

8. SOLUTION
 Wireless technology is ruling worldwide and has invaded the
medical area with wide range of scope and capabilities
 To monitor continuous Medicare conditions of patient using
existing wireless technologies were quite convoluted.
 To overcome this, we are proposing a change in wireless
sensor technology by designing a biomedical monitoring
device comprised of AD8232 SparkFun Single Lead Heart
Rate sensors to acquire the information regarding heart rate
which is sent to a personal vitality measurement system and
further transmit this information on an IOT server which is
user accessible over the internet.

9. HARDWARE COMPONENTS
• AD8232 Spark Fun Single Lead Heart Rate Monitor Module
• Ag-Agcl electrodes and 3 wire lead
• Node MCU (WI-FI Module)

10. HARDWARE COMPONENTS (optional)
• Arduino Uno with cable
• Fourth order low pass filter circuit with cut-off
frequency 40Hz (fabricated by ourselves)

11. SOFTWARE REQUIRED
•Arduino IDE
•Pycharm Jetbrains community edition
•MATLAB/ GNU OCTAVE
•ANDROID STUDIO
•FileZilla

12. OPERATION OF THE PROTOTYPE
BLOCK DIAGRAM OF PROTOTYPE

13. OPERATION OF THE
PROTOTYPE
• We have used AD8232 SparkFun Single Lead Heart Rate
Monitor Module to measure the electrical activity of the heart
(Electrocardiogram or ECG). A filter circuit is designed and
connected to the in input of the sensor module to extract,
amplify and filter small bio potential signals in the present of
noisy conditions.
• The analog data obtained from the sensor is fetched to an
NodeMCU board. We can observe the ECG waveform in the PC
using Arduino IDE serial plotter as well as using the MATLAB
GUI.

14. OPERATION OF THE
PROTOTYPE
• Analysis of the obtained ECG curve is done using python and
MATLAB. We can analyse the curve to conclude whether the
person has any heart disease or not and if yes what type of
disease the person has. We can also determine the heart rate of
the person from the ECG curve.
• We have created a server sub domain. The continuous real time
data obtained from the sensor is uploaded to the server using
NodeMCU module.
• The uploaded data is captured from the server in the receiving
end situated anywhere in the world. Doctor from anywhere of
the world can access the real time data and by observing and
analysing the ECG curve in the MATLAB GUI or Python or
mobile app, he/she can diagnose the patient.

15. SENSOR TO APPLICATION

16. SENSOR TO APPLICATION

17. OPERATION OF THE PROTOTYPE
ACTUAL HARDWARE SETUP

18. OPERATION OF THE PROTOTYPE
ECG CURVE VISUALIZED IN ARDUINO IDE

19. OPERATION OF THE PROTOTYPE
ECG CURVE VISUALIZED IN SERVER

20. OPERATION OF THE PROTOTYPE
ANALYSED ECG CURVE IN PYTHON AND MATLAB

21. HEART DISEASES DIAGNOSED BY
ANALYZING ECG CURVE
 Hypokalaemia
 Hyperkalaemia
 Right atrial enlargement
 Myocardial infarction
 Myocardial Ischemia
 Coronary Artery disease
 Rheumatic fever
 Atherosclerotic heart disease
 Wolf Parkinson White Syndrome
 Bradycardia
 Tachycardia
 Heart block tendency
 Ventricular Hypertrophy

22. SL.
NO.
CLINICAL
SIGNATURES
TYPICAL
VALUES
NOMINAL
LIMIT(+-)
NAME OF DISEASE
(VALUE>TYPICAL)
NAME OF DISEASE
(VALUE<TYPICAL)
1 P-wave Amplitude 0.15mV 0.05mV 1. HYPOKALEMIA
2. RIGHT ATRIAL
ENLARGEMENT
HYPERKALEMIA
2 S-T Segment
Amplitude
0-0.2mV xxxxxxxxxxx 1. ACUTE MYOCARDIAL
INFARCTION
1. MYOCARDIAL
ISCHEMIA
2. HYPOKALEMIA
3 Q-R-S Complex wave
Amplitude
1.2mV 0.5mV 1. MYOCARDIAL infarction xxxxxxxxxxxxxxxxxxxxxx
4 T-wave Amplitude 0.3mV 0.2mV 1. MYOCARDIAL ISCHEMIA
[value>-0.1mV(inverted)]
2. HYPOKALEMIA [value is
within
-0.1mV-0.1mV(flattened)]
xxxxxxxxxxxxxxxxxxxxxx
5 Q-wave Amplitude 0.5mV xxxxxxxxxxx xxxxxxxxxxxxxxxxxxxxxxxxx 1. CORONARY ARTERY
DISEASE
6 P-R interval 120mS 20mS 1. HYPOKALEMIA
2. RHEUMATIC FEVER
3. ATHEROSCLEROTIC HEART
DISEASE
4. HEART BLOCK
1. WOLF PARKINSON
WHITE SYNDROME
7 Q-R-S interval 100mS 20mS VENTRICULAR HYPERTROPHY
HEART FAILURE(Chances 14%-
47%)
LEFT BUNDLE BRUNCH BLOCK
OF HEART
xxxxxxxxxxxxxxxxxxxxxx
8 R-R peak interval 0.75S-0.85S xxxxxxxxxxx 1. BRADYCARDIA (>=1S)
2. HEART BLOCK TENDENCY
(>=1.2)
1. TRACHYCARDIA
(<=0.3S)

23. EFFORTS AND COSTS:
 Person Hours – 3 person*150(6hrs*5days*5weeks) =450 hrs.
 Cost- Hardware- Rs. 2000-2500

24. IMPACT
• Clinical Care

25. IMPACT
• Remote Patient Monitoring

26.  Device management.
 Technical malfunction.
 Data security .
 Active monitoring.
 Database management.