Development of ECG and EMG platform with IMU to eliminate the motion artifacts found in measurements

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Journal Title

Journal ISSN

Volume Title

Sähkötekniikan korkeakoulu | Master's thesis

Date

2018-06-18

Department

Major/Subject

Micro- and Nanoelectronic Circuit Design

Mcode

ELEC3036

Degree programme

NanoRad - Master’s Programme in Nano and Radio Sciences (TS2013)

Language

en

Pages

91+6

Series

Abstract

The long term measurement and analysis of electrophysiological parameters is crucial for diagnosis of chronic diseases, and to monitor critical health parameters. It is also very important to monitor physical fitness improvement, or degradation level, of human beings where physical fitness is entirely critical for their work, or of more vulnerable members of society such as senior citizens and the sick. The state-of-the-art technological developments are leading to the use of artificial intelligence in the continuous monitoring and identification of life-threatening events in the daily life of ordinary people. However, these ambulatory measurements of electrophysiological parameters leads to drastic motion artifacts because of the test subject’s movements. Therefore, there is a dire need for the development of both hardware and software solutions to address this challenge. The scope of this thesis is to develop a hardware platform, by using off-the-shelf discrete and IC electronic components, to measure two electrophysiological parameters, electrocardiogram (ECG) and electromyogram (EMG), with an additional motion sensor inertial measurement unit (IMU) comprising nine degrees of freedom. The ECG, EMG and IMU data will be collected using the developed measurement platform from various predefined day-to-day routine activity events. A Bluetooth interface will be developed to transmit the data wirelessly, and record it on a laptop for further real-time processing. The resources of the electrical workshop and measurement lab at Aalto University will be used for the development, assembly, testing and finally for research of the measurement platform. The second aspect of the study is to prepare, process and analyze the recorded ECG and EMG data by using MATLAB. Various filtering, denoising, processing and analysis algorithms will be developed and executed to extract the features of the ECG and EMG waveform structures. Finally, graphical representations will be made for the resulting outputs of the aforementioned techniques.

Description

Supervisor

Halonen, Kari

Thesis advisor

Halonen, Kari

Keywords

electrocardiography, electromyography, inertial measurement unit, motion artifact

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