Health Monitoring System using IoT.doc

Raspberry-Pi based health monitoring using heartbeat and Pulse Sensor
Health monitoring has always been a promising application for the Internet of Things
(IoT). By using the right technology we no longer have to depend on our general routine
health check up or our local physicians to assess our body. Sensors can be used to measure all
your body vitals and this information can be shared remotely in real time for a doctor from
other part of the world to diagnosis you or perhaps an AI could crunch all the numbers and
diagnosis your problem. Sounds futuristic right? But we are gradually moving towards it and
we are not very far from having remote IoT Robotic Arms performing surgery on us. While
we progress with that, in this session we will build a Raspberry Pi heart rate monitor to
measure the heart rate of a remote patient and display it on Processing IDE. Previously we
have also built a Heart Rate Monitor using Arduino and ESP8266 and uploaded the values
to Thingspeak.
Material Required:
The following are the components required to build your own, patient monitoring system
using Raspberry Pi.
1. Raspberry Pi

2. Pulse Sensor
3. ADS1115 ADC module
4. Jumper wire
5. Power supply or power bank
Pulse Rate Sensor:
Before we get into the actual project let’s take a look at how the Pulse Rate sensor works.
The working of the Pulse/Heart beat sensor is very simple. The sensor has two sides, on one
side the LED is placed along with an ambient light sensor and on the other side we have some
circuitry. This circuitry is responsible for the amplification and noise cancellation work. The
LED on the front side of the sensor is placed over a vein in our human body. This can either
be your Finger tip or you ear tips, but it should be placed directly on top of a vein.
Now the LED emits light which will fall on the vein directly. The veins will have blood flow
inside them only when the heart is pumping, so if we monitor the flow of blood we can
monitor the heart beats as well. If the flow of blood is detected then the ambient light sensor
will pick up more light since they will be reflect ted by the blood, this minor change in
received light is analyzed over time to determine our heart beats. In this project the pulse
sensor works as a heartbeat sensor for Raspberry Pi.
Signal wire shown in violet, red and black color respectively. In our project the sensor will be
powered by the 3.3V pin of Arduino and the signal pin will be connected to Raspberry pi
through the ADS115 ADC module since Raspberry Pi by default cannot read Analog voltage.
Circuit Diagram:
The complete circuit diagram for IoT patient monitoring system using Raspberry Pi is shown
below.

As you can see we have used the ADS115 ADC module with Pulse sensor and the pulse
sensor is connect to Pi through I2C communication, so that we can measure heartbeat on
Raspberry Pi. Below are the connections:
 Signal pin of pulse sensor -> A0 of ADC Module
 Vcc pin of pulse sensor -> 3.3V of Raspberry
 GND pin of pulse sensor -> GND of Pi
 Tx of RPI-> Rx of RPI
 GND of ADC module -> GND of RPI
 VCC of ADC Module -> +5v Of RPI
 SCL and SDA of ADC module -> SCL and SDA of RPI

Installation and configuration
Since the ADC module communicates in I2C and we use UART for serial communication we
have to, enable UART and I2C of raspberry pi by using raspi-config command in the shell as
show below.
Now select Interfacing Options and press enter.

Now select I2C and press enter
Now select Yes and press enter

Now press enter by selecting ok
Now enable Serial by selecting Serial and press enter

Now select no and press enter for disabling the login shell over serial.
Now select Yes and press enter for enable the serial.

Now select ok and press enter.
Now Select finish and press enter

Now select Yes and press enter for reboot.
Now install i2c packages
sudo apt-get install -y python-smbus
sudo apt-get install -y i2c-tools

Now test and get I2C address of connected device by using given command:
sudo i2cdetect -y 1
Now install the ads1115 python library for ADC module by using given commands
sudo apt-get update
sudo apt-get install build-essential python-dev python-smbus git
cd ~
git clone https://github.com/adafruit/Adafruit_Python_ADS1x15.git

cd Adafruit_Python_ADS1x15
sudo python setup.py install
Installing Processing on Raspberry Pi
Now Install Processing onto existing installation by using given command:
curl https://processing.org/download/install-arm.sh | sudosh

Now we can see the processing icon in the raspberry pi menu:

Here we need to run pulse_sensor python code then processing code given at the end of this
article. And then we will see the results as shown in the image below

Raspberry Pi Python code for a Measuring Heartbeat
Complete processing and python code is given below or it can also be downloaded from here.
Also check the demonstration video given below.
Code
Python Code:
import Adafruit_ADS1x15
import serial
import time
rate = [0]*10
amp = 100
GAIN = 2/3
curState = 0
stateChanged = 0
ser = serial.Serial ("/dev/ttyS0", 9600)
def send_to_prcessing(prefix, data):
ser.write(prefix)
ser.write(str(data))
ser.write("n")
def read_pulse():
firstBeat = True
secondBeat = False
sampleCounter = 0
lastBeatTime = 0
lastTime = int(time.time()*1000)
th = 525
P = 512
T = 512
IBI = 600
Pulse = False
adc = Adafruit_ADS1x15.ADS1015()
while True:
Signal = adc.read_adc(0, gain=GAIN)
curTime = int(time.time()*1000)
send_to_prcessing("S",Signal)
sampleCounter += curTime - lastTime
lastTime = curTime
N = sampleCounter - lastBeatTime
if Signal >th and Signal > P:
P = Signal
if Signal <th and N > (IBI/5.0)*3.0 :
if Signal < T :
T = Signal
if N > 250 :
if (Signal >th) and (Pulse == False) and (N > (IBI/5.0)*3.0) :
Pulse = 1;
IBI = sampleCounter - lastBeatTime
lastBeatTime = sampleCounter
if secondBeat :
secondBeat = 0;

for i in range(0,10):
rate[i] = IBI
if firstBeat :
firstBeat = 0
secondBeat = 1
continue
runningTotal = 0;
for i in range(0,9):
rate[i] = rate[i+1]
runningTotal += rate[i]
rate[9] = IBI;
runningTotal += rate[9]
runningTotal /= 10;
BPM = 60000/runningTotal
print("BPM:" + str(BPM))
send_to_prcessing("B", BPM)
send_to_prcessing("Q", IBI)
if Signal <th and Pulse == 1 :
amp = P - T
th = amp/2 + T
T = th
P = th
Pulse = 0
if N > 2500 :
th = 512
T = th
P = th
lastBeatTime = sampleCounter
firstBeat = 0
secondBeat = 0
print("no beats found")
time.sleep(0.005)
read_pulse()

Health Monitoring System using IoT.doc

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