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Arduino and HRV Analysis

This page contains resources for the "Developing STEM skills using Arduino and heart rate variability analysis" workshop as presented at the 2018 Deakin STEM Education Conference.

Table of Contents

  1. Introduction
    1. Physiology
    2. Measurement
  2. Components
  3. Software setup
  4. Hardware setup
    1. Connecting the Arduino board
    2. Connecting the ECG kit
    3. Attaching the ECG electrodes
  5. Programming
  6. Data analysis
  7. Conclusion

Introduction

With the introduction of wearable sensors and the Internet of Things (IoT), the use of physiological signals to continuously assess our mental and physical state is growing rapidly. This field offers an exciting opportunity to learn a range of science, technology, engineering and mathematics (STEM) skills using widely available low-cost devices such as the Arduino.

In this workshop, we'll show you how to record your heart rate using the Arduino platform and describe a series of practical activities based on heart rate variability (HRV) analysis. Targeted at senior secondary and first year undergraduate students, this workshop aims to inspire you to develop your STEM skills and learn how they can be used to understand the electrical rhythms of our bodies.

Physiology

To begin, let's recap the basics of what determines our heart rate. The main system responsible for coordinating this task is known as the autonomic nervous system or ANS. The ANS is responsible for a large range of bodily functions including heart rate, digestion, respiration and more. The two main branches of the ANS which relate to heart rate are known as the sympathetic and the parasympathetic nervous systems.

The sympathetic nervous system is associated with our "fight-or-flight" response and acts to increase the heart rate, while the parasympathetic nervous system is associated with "rest-and-digest" activities and acts to decrease the heart rate. These two systems exert control over our heart rate by sending signals to a bundle of cells in the heart known as the sinoatrial node.

The sinoatrial node, also known as the heart's natural pacemaker, is a group of cells that produce regular electrical impulses which cause the heart to contract and pump blood throughout the body. Based on the timing of these heart contractions, we can determine an enormous amount of information about a person, including their emotional state, stress levels, sleep quality and more.

Measurement

So how do we measure the heart rate? There are many different ways to achieve this, but for the purposes of this workshop we are going to focus on measuring the electrical activity produced by the heart and how it can be interpreted.

To understand this process, we first need to recap a bit of physics. As you might know, all materials are made of atoms, which are in turn made of smaller particles called protons, neutrons and electrons.

Materials are said to have positive charge when they contain fewer electrons than protons and negative charge when they contain more electrons than protons. The flow of electrons from one material to another is what we call electricity. It can be described using the following terms:

Current – The flow of electrons between a negatively charged material and a positively charged one.

Voltage – The difference between the charge in one material compared to another.

Resistance – A measure of whether it is easy or hard for electrons to move through a particular material.

Current, voltage and resistance are related by an equation known as Ohm's law:

\[ V = I \times R\]

V – Voltage in Volts (V)
I – Current in Amperes (A)
R – Resistance in Ohms (Ω)

To measure the electrical activity of the heart, we are going to look at the difference in voltage measured at different points across the body.

Components

To do this, we're going to need a few pieces of equipment as given in the table below:

Arduino Uno R3 $12.00 AUD
DFRobot Gravity ECG Kit $28.96 AUD
Plug to Plug Jumper Cables $3.03 AUD

Prices updated as of 01/01/2019

Software setup

Once you've got everything ready, let's start by setting up the Arduino software:

  1. Go to the Arduino Software Downloads webpage.
  2. Scroll to "Download the Arduino IDE".
  3. Press the download for your operating system (e.g. Windows/Mac/Linux).
  4. Double click and install the downloaded file.

Hardware setup

Connecting the Arduino board

  1. Plug the USB cable into the Arduino board.
  2. Plug the other end of the USB cable into your computer.

Connecting the ECG kit

  1. Plug one end of the red wire into the 5V socket.

  2. Plug one end of the black wire into the GND socket.

  3. Plug one end of the blue wire into the A0 socket.

  4. Plug the other end of the red, black and blue wires into the Gravity ECG module.

  5. Plug the grey ECG lead (looks like a headphone jack) into the Gravity ECG module.

Attaching the ECG electrodes

  1. Place the three ECG patches on a hard surface with the metal button facing up. Do not remove the adhesive backing yet.

  2. Press the three ECG clips (i.e. green, red and yellow leads) down firmly onto each of the three ECG patches.

  3. Remove the adhesive backing from each ECG patch and place them onto your arms as shown below.

Programming

For this section you'll need to download the following file: ecg.ino

  1. Once ecg.ino has been downloaded, double click the file to open it in the Arduino IDE.

  2. After the Arduino software has opened, navigate to Tools and ensure the Arduino/Genuino Uno board is selected as shown below.

  3. Next, ensure the correct COM port is selected. The correct COM port should list the name of the Arduino device in brackets as shown below.

  4. Next, check that the Serial Plotter is set to the correct baud rate by first pressing Serial Plotter and then setting the baud rate to 115200 baud in the popup window.

  5. Finally, send the code to the Arduino board by clicking the Upload button.

  6. If everything has been set up correctly, you should now see your ECG appear in the serial plotter window as shown below.

  7. Data analysis

    Now that we are receiving the ECG data on the Arduino, it's time to start our analysis. Firstly, from the ECG waveform, we can highlight a few features in each cardiac cycle as shown below:

    These features, known as the P wave, QRS complex and T wave, consist of different areas in the heart being electrically activated during each heartbeat.

    The P wave results from electrons (in the form of ions such as calcium and potassium) travelling from the sinoatrial node located in the upper right atrium towards the atrioventicular node which connects the atria and ventricles. The QRS complex then results from electrons flowing through the cardiac muscle as the ventricles contract (depolarisation), followed finally by the T wave which results from the relaxation of the cardiac muscle (repolarisation). A great animation of this process is shown below (click here for the full video).

    Our heart rate is determined by the time intervals between each R peak, where its value in beats per minute (or bpm) is given by the following formula:

    \[ \text{Heart rate (in bpm)} = \frac{60}{\text{Time between r peaks (in seconds)}}\]

    To calculate your heart rate using the Arduino, try uploading the following code: heartrate.ino

    Once you have this code running, you should see your heart rate displayed alongside your ECG. If you don't see anything, first try adjusting the ecgOffset value so that your ECG reading is centred around a value of 0. Next, adjust the upperThreshold to a value less than your smallest R peak but greater than your largest T wave and the lowerThreshold to a value slightly below this. If everything is set up correctly, your plot should look like the below where the red line indicates your heart rate in bpm. Additionally, you should see the inbuilt LED on the Arduino blink every time a heart beat is detected.

    Now that we are reading our heart rate, it's time to dive a bit deeper into HRV analysis. This field encompasses a huge range of techniques, so for this workshop we are going to focus on calculating the following features:

    • AVNN - The mean of heart beat intervals in each 5 minute reading.

    • SDNN - The standard deviation of heart beat intervals in each 5 minute reading.

    • SDSD - The standard deviation of differences between adjacent heart beat intervals in each 5 minute reading.

    For the final activity of this workshop, try writing code to calculate these three features and take your HRV measurements for 5 minutes immediately before and after completing one of the following activities:

    • Jog on the spot for 1 minute

    • Box breathe for 1 minute

    • Watch an exciting YouTube video

    Conclusion

    Congratulations! You now know how to measure and analyse the electrical activity of your heart. For extended activities, you could try making your heart rate monitor wireless using the ESP8266 microcontroller or check out this free book on the theory of bioelectromagnetism. If you're feeling really excited, you could even try investigating some more advanced HRV features as available in the PhysioZoo toolkit. We hope you have enjoyed this workshop and don't be afraid to leave a comment below if you have any questions.

    Acknowledgement

    This workshop was developed in collaboration between the following authors and institutions:

    Emerson Keenan\(^1\), Mehrnaz Shoushtarian\(^2\), Chandan Kumar Karmakar\(^{1,3}\), Marimuthu Palaniswami\(^1\)

    \(^1\) Department of Electrical and Electronic Engineering, The University of Melbourne, Parkville, VIC 3010, Australia
    \(^2\) The Bionics Institute, East Melbourne, VIC 3002, Australia
    \(^3\) School of Information Technology, Deakin University, Burwood, VIC 3125, Australia

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