IoT Based Remote Patient Vital Body Signs using Arduino Nano-33:
in the human body there are four major parameters that we need to be aware of, they are body temperature, heart rate, breath rate, blood pressure, and due to COVID, oxygen saturation has become a major parameter that we need to be aware of.
Here we making a simple Arduino Nano 33 IoT-based device with multiple sensors. The device can measure some vital parameters of the human body. The device will be like a DIY multi-para monitor that you see in ICUs, a lot simpler and made of cheap sensors not meant for actual medical use. We will be using the new Arduino Nano 33 IOT for this purpose and we will try to make this device as simple as possible.
Components Required:
1. Arduino Nano 33 IOT
2. MLX90614 (Digital Non-Contact Infrared Thermometer)
3. AD8232 (Heart Rate Monitor)
4. MAX30100 (Pulse Oximeter and Heart-Rate Sensor)
5. Audio (with Mic)
About Arduino Nano 33 IoT Module:
Arduino Nano 33 IoT is a relatively new Arduino board, It is a direct upgrade to the original Arduino Nano, and currently available on the Arduino Store. It is cheaper than an original Arduino Nano, but the Nano is widely available at much cheaper rates as a clone. So, should you buy this new board when you could get a clone of the earlier generation?
If you want to prototype with Wi-Fi and BT with some sensors in a compact form factor, it’s recommended to go for it. From this standpoint, buying all the items separately and interfacing them is going to probably cost you more time and money than the Nano 33 IoT.
Futures of Arduino Nano 33 IoT Module:
1. The board’s main processor is a low-power Arm Cortex-M0 32-bit SAMD21.
2. Wi-Fi 2.4G and Bluetooth connectivity is provided by the U-Blox NINA-W102 low-power chipset.
3. The Wi-Fi / BT module antenna is made in the form of a metal fitting, protected from anti-vibration by a drop of thermal glue.
4. Microchip ATECC608A crypto chip ensures secure communication, 6 axis IMU LSM6DS3
MAX30100 – Pulse Oximeter and Heart-Rate Sensor:
The MAX30100 is also a Microchip based sensor module. It uses a concept called Photo Plethysmography to measure vital stats, and as output, it gives a PPG graph.
As you can see, an IR/Red/Green LED shines on the subject’s finger. Depending on the heartbeats, oxygen diffusion in the blood, and a few other parameters, the value or rate of absorption of the incident wave changes. By identifying these alterations, we can determine the oxygen level.
The transmitted wave is then measured by a receiver which gives a voltage signal depending on the amount of light received. When light travels through biological tissues, it is absorbed by bones, skin pigments, and both venous and arterial blood. Since light is more strongly absorbed by blood than the surrounding tissues, the changes in blood flow can be detected by PPG sensors as changes in the intensity of light.
The voltage signal from PPG is proportional to the quantity of blood flowing through the blood vessels. Even small changes in blood volume can be detected using this method, though it cannot be used to quantify the amount of blood. A PPG signal has several components including volumetric changes in arterial blood which is associated with cardiac activity, variations in venous blood volume which modulates the PPG signal, a DC component showing the tissues’ optical property, and subtle energy changes in the body.
The MAX30100 sensor has an IR and red LED. Generally, heart rate and SPO2 parameters are measured, we will try measuring an additional parameter – HRV or heart rate variability.
MLX90614 – Body Temperature Sensor:
The MLX90614 body temperature sensor is from Melexis, which uses IR technology to measure the body temperature of a person. Commonly referred to as pyrometry, this sensor is like a single pixel thermal camera but has a very small range of less than 3 cm.
Also, like other IR devices, the sensor reading error increases with the distance between the subject and the sensor.
AD8232 ECG Sensor
The AD8232 is a simple heart rate sensor that can be charted as an ECG. ECG stands for electrocardiogram. This sensor outputs its signal as an analog signal. The 3.5mm jack is used for biomedical pad connection.
Analog MIC Module
This is a simple sensor that records audio amplitude and outputs them as analog variations. This is useful in measuring respiratory signals but it requires a lot of signal processing and filtering.
128X64 OLED Display:
We will be using a 1.3” OLED I2C display for this project. There are a lot of generic ones in the market, so it might be possible that your OLED might be a bit different from mine. The Uglib2 library that we will be using has support for almost every display you can come across, so it’s very simple to interface any OLED display with this library.
Circuit diagram for Remote Patient Monitoring System:
The complete schematic diagram to build the Remote Health Monitoring System is shown below.
The schematic above shows all the necessary connections with the Arduino Nano 33 IoT. The two types of sensors used are analog (mic, OLED display, and AD8232) and I2C (mlx90614 and MAX3010X). The Arduino
Nano 33 IoT pins used are:
1. A0 – Analog output of ECG module AD8232.
2. A1 – Analog output of mic module.
3. A4 – SDA..
4. A5 – SCL.
While working with the sensor and this board, you need to keep some things in mind. The working voltage in the above schematic is 3V3, as the ECG module operates at 3V3 and we don’t want unnecessary voltage conversions. The resistors used in the above schematic are 4.7k. They should suffice even for the 3V3 working voltage. We will not be using the extra pins LO+, LO- or to reduce unnecessary complexity since this project already has many sensors working together.
I would recommend that you place the MLX90614 and MAX3010X sensors such that they coincide and you can cover both of them together with a single finger at the same time. As for the coding part, I will try my best to explain it concisely.
Arduino Code to Measure and Monitor Vital Signs:
we need to install the required libraries, and you can find almost all of those necessary libraries in the Arduino board manager and we will install the libraries from there, we need to install the following libraries.
Arduino SAMD boards
Arduino_LSM6DS3 or Sparkfun LSM6DS3 Breakout (for advanced usage)
Arduino WifiNINA
Arduino BLE
#include <Wire.h>
#include "MAX30100_PulseOximeter.h"
#include "MAX30100.h"
#include <Adafruit_MLX90614.h>
#include <Adafruit_GFX.h>
#include <U8x8lib.h>
#include <avr/dtostrf.h>
#define REPORTING_PERIOD_MS 500 // parameters in milli seconds
#define DISPLAY_INTERVAL 5 //update rate for the i2c display = REPORTING_PERIOD_MS*DISPLAY_INTERVAL
#define COMPENSATION 5 //compensation in object temperature. Different body parts have different temperatures. Fingers are around 5 degF lower than core body temperature// objects
PulseOximeter pox; //this offers spo2 and hr calculation
Adafruit_MLX90614 mlx = Adafruit_MLX90614();
U8X8_SH1106_128X64_NONAME_HW_I2C u8x8(/* reset=*/ U8X8_PIN_NONE);
MAX30100 sensor;
//variables
uint32_t tsLastReport = 0;
int hr, spo2, count = 0, flag = 0, PatientID = 0;
float ambient, object, hrv;
long time1 = 0, time2 = 0;
uint16_t ir = 0, red = 0, ecg = 0, mic; ;
char str_hrv[10], str_object[10], str_ambient[10], str_ir[10], str_red[10];
// Callback (registered below) fired when a pulse is detected
void onBeatDetected()
{
time1 = micros() - time2;
time2 = micros();
}
void setup()
{
//display connected
u8x8.begin();
u8x8.setPowerSave(0);
u8x8.setFont(u8x8_font_chroma48medium8_r);
//pinMode(10, INPUT); // Setup for leads off detection LO +
//pinMode(11, INPUT); // Setup for leads off detection LO -
Serial.begin(115200);
/*
while (!Serial)
{
; // wait for serial port to connect. Needed for native USB port only
}
if (!pox.begin(PULSEOXIMETER_DEBUGGINGMODE_RAW_VALUES)) {
//Serial.println("FAILED");
for(;;);
}
else
{
//Serial.println("SUCCESS");
}
pox.setIRLedCurrent(MAX30100_LED_CURR_11MA);
// Register a callback for the beat detection
pox.setOnBeatDetectedCallback(onBeatDetected);
mlx.begin();
time2 = micros();
}
void loop()
{
// Make sure to call update as fast as possible
pox.update();
sensor.update();
//reading continuous functions (signals) every loop
while (sensor.getRawValues(&ir, &red))
{
}
ecg = analogRead(A0);
ecg = map(ecg, 250, 500, 0, 100);
mic = analogRead(A1);
delay(1);
if (millis() - tsLastReport > REPORTING_PERIOD_MS)
{
hr = pox.getHeartRate();
spo2 = pox.getSpO2();
ambient = mlx.readAmbientTempF();
object = mlx.readObjectTempF() + COMPENSATION;
hrv = (60000000/hr - (float)time1)/1000;
//send_serial();
tsLastReport = millis();
count++;
flag = 0;
}
if ((count%DISPLAY_INTERVAL == 0) && (flag != 1))
{
flag = 1; //This flag makes sure the display is updated only once every DISPLAY_INTERVAL seconds
Wire.end();
send_display();
Wire.begin();
}
Telemetry();
}
r
void send_serial()
{
Serial.print("bpm / SpO2:");
Serial.print("Heart rate:");
Serial.print(hr);
Serial.print(spo2);
Serial.print("% / hrv:");
Serial.print(hrv);
Serial.print("ms / Ambient:");
Serial.print(ambient);
Serial.print("*F / tObject = ");
Serial.print(object);
Serial.println("*F");
}
//display print function
void send_display()
{
u8x8.clearDisplay();
u8x8.setCursor(0,1);
u8x8.print("HRV:");
u8x8.print(hrv);
u8x8.print(" ms");
u8x8.setCursor(0,2);
u8x8.print("SpO2:");
u8x8.print(spo2);
u8x8.print(" %");
u8x8.setCursor(0,3);
u8x8.print("HR:");
u8x8.print(hr);
u8x8.print(" bpm");
u8x8.setCursor(0,4);
u8x8.print("Temp:");
u8x8.print(object);
u8x8.print(" degF");
u8x8.setCursor(0,5);
u8x8.print("ecg:");
u8x8.print(ecg);
u8x8.setCursor(0,6);
u8x8.print("mic");
u8x8.print(mic);
//delay(200);
}
//serial telemetry for edge impulse data forwarder
void Telemetry()
{
char buffer[150];
dtostrf(hrv, 4, 2, str_hrv);
dtostrf(object, 4, 2, str_object);
dtostrf(ambient, 4, 2, str_ambient);
dtostrf((float)ir/100, 5, 2, str_ir);
dtostrf((float)red/100, 5, 2, str_red);
sprintf(buffer,"%d,%d,%d,%d,%s,%s,%s,%s,%s,%d,%d",PatientID,count/10,hr,spo2,str_hrv,str_object,str_ambient,str_ir,str_red,ecg,mic);
Serial.println(buffer);
}
