Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Jul 13, 2022
Date Accepted: Oct 22, 2022
Date Submitted to PubMed: Oct 24, 2022
Motion Artifact Reduction in Electrocardiographic Signals through Redundant Denoising Independent Component Analysis Method for Wearable Health Care Monitoring Systems
ABSTRACT
Background:
The quest for improved diagnosis and treatment in home health care models has led to the development of wearable medical devices for outpatient vital signs monitoring. An accurate signal and a high diagnostic yield are critical for the cost-effectiveness of wearable health care monitoring systems and their widespread application in resource-constrained environments. Despite technological advances, the information acquired by these devices can be contaminated by Motion Artifacts leading to misdiagnosis or repeated procedures with increases in associated costs. This makes it necessary to develop methods to improve the quality of the signal acquired by these devices.
Objective:
This article presents a new method to reduce Motion Artifacts in Electrocardiographic signals.
Methods:
The method is based on the redundant and simultaneous acquisition of Electrocardiographic signals and movement information, multichannel processing, and performance assessment considering the information contained in the signal waveform.
Results:
The proposed method significantly reduced Motion Artifacts, showing better performance, and introducing a smaller distortion in the interest signal compared to other methods. Finally, the performance of the proposed method was compared with Wavelet Shrinkage and the Wavelet Independent Component Analysis through the assessment of Signal-to-Noise Ratio, Dynamic Time Warping, and a proposed index based on the signal waveform evaluation with Ensemble Average Electrocardiographic.
Conclusions:
A more accurate signal substantially improves the diagnostic yield of wearable devices. A better yield improves the devices' cost-effectiveness and contributes to their widespread application. This is an advance in the path to converting wearable devices into medical monitoring tools that can be used to support the diagnosis and monitoring of cardiovascular diseases. Clinical Trial: The ethics committee for human studies of the Universidad de Antioquia approved the register protocol (Approval 16-59-711).
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.