Projects:2020s2-7451 Analysing Health Data from Wearables

Heart rate (HR) and respiratory rate (RR) are important physiological parameters that could be used to indicate ones health and abnormalities in these parameters could be an indicator of serious illness. Therefore, many different methods have been proposed for automatic monitoring of HR and RR. In this study, we would use photoplethysmogram (PPG) signal to extract HR and RR data through development of algorithms in Matlab. Firstly, digital filtering would be used to detect and distinguish noisy signal and also motion artifact from a raw PPG signal. Then, the filtered signal would be extracted to gain HR and RR data.

Project team

Project students

• Amirahtul Nazihah Amir
• Bin Dai
• Jiaping Wang

Supervisors

• Associate Professor Mathias Baumert
• Associate Professor Brian Ng

Introduction

PPG is a simple optical technique used to detect the volumetric changes in the blood. It is a low cost and non-invasive method that makes a measurement on the surface of the skin. Different from electrocardiogram (ECG), PPG does not focus on the electrical pulses that cause the heart to beat, but rather on the effect that the beating has on blood vessels. With every beat of the heart, blood would be pumped out of the heart into blood vessels putting pressure on the vessel wall and causing them to dilate. These blood vessel would relax again between two heartbeats. In this study, a camera-based PPG is used as it enables remote vital signal monitoring by using cameras. This would be cost-efficient since cameras are available in an everyday item such as a smartphone. By lighting fingertip for 60 seconds with the flashlight of a smartphone camera, minuscule changes in the amount of blood that flows through the dilating and relaxing capillaries would be measured based on the amount of light that is reflected back to the camera. When the capillaries are dilated, meaning it contains a lot of blood, a lot of the light would be absorbed by the blood and therefore just a little would be reflected. Vice versa, when the capillaries are in relax condition, not much of the light would be absorbed and hence there would be more light reflected back to the camera.

Objectives

The overall objective of this project is to design a software system to analyse the health data from noisy photoplethysmography (PPG). The software system has the following specific goals:

1. to detect and remove the artifacts in the original PPG signals;
2. to monitor the subjects’ health parameters such as the heart rate (HR) and the respiration rate (RR) from the PPG waveforms;

Additionally, this project is aimed to develop a graphical user interface (GUI) system. This GUI design is aimed to display both original and noisy PPG waveforms. In addition, it shall allow users to choose which ranges of signals they consider as artifacts. The calculated HR and RR analysed from the PPG waveforms are displayed to them as well.

Motivation and Significance

Nowadays, one of the significant causes of death worldwide is a disease according to . For the poor nations such as Liberia and Zimbabwe, there are not sufficient diagnosis equipment and treatment instrument. Consequently, it could cause large numbers of patients’ death. Even for some developed and developing nations, there are some impoverished areas that do not have enough medical equipment or hard to move to the medical centre due to mobility problems as stated in [2]. One of the main functions of PPG is to diagnose human fitness and illness via HR and RR calculation [3]. HR and RR are two of the vital human signs which are effective for diagnosing. PPG could be not only detected by specific instrument but also by some wearable device such as smartphones and smartwatch as stated in Section 2.1 below. Therefore, the diagnosis via wearable device PPG is convenient and inexpensive for the needed personals. Overall, the main significance of this project is to help the patients with mobility issues or who live in some area which does not have sufficient diagnosis equipment. Therefore, they could know if they have any fitness disease as early as possible and receive treatment as early as possible.