Abstract

This study proposes a wearable system that can measure electrocardiogram (ECG) signals reliably in an environment with high motion induced noise. This system employs a motion artifact extraction method based on a triple-axis accelerometer attached to each electrode independently to remove motion artifact from ECG signals with high performance. Recursive Least Square (RLS) and Least Mean Square (LMS) algorithms remove extracted noise from the source signals, thereby obtaining a mean square error (MSE) of 0.0166 when using RLS and 0.0160 when using LMS. This means that the performance improved respectively by approximately 5.1% and 8.6% compared to that of the recently developed ECG monitoring system.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.