A stochastic fusion technique for removing motion artefacts from the measurements of a wireless ECG

Wireless electrocardiograms are useful for several practical applications in the healthcare domain. However, their usefulness is often limited by the quality of data that can be extracted from them. One of the main factors affecting the quality of ECG data is the inclusion of movement induced artefa...

Full description

Saved in:
Bibliographic Details
Published in2016 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI) pp. 449 - 454
Main Author Dargie, Waltenegus
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2016
Subjects
Accelerometers
Electrocardiography
Mathematical model
Motion measurement
Sensors
Wireless communication
Wireless sensor networks
Online AccessGet full text

Cover

More Information
Summary:Wireless electrocardiograms are useful for several practical applications in the healthcare domain. However, their usefulness is often limited by the quality of data that can be extracted from them. One of the main factors affecting the quality of ECG data is the inclusion of movement induced artefacts. In this paper we propose an adaptive filter to improve the quality of measurements. We propose to use motion or inertial sensors to capture the movements which affect the electrodes of a wireless ECG. Thus, we regard measurements from a 3D accelerometer and a 3D gyroscope as indication of the magnitude of noise artefacts in the outputs of a wireless ECG and use them to estimate and remove the movement artefacts. The paper presents the design and implementation of the filter, which we used to improve actual measurements we took whilst different subjects carried out various everyday activities (walking, running, riding a bicycle, and climbing up and down a staircase).
DOI:10.1109/MFI.2016.7849529