A Wavelet Adaptive Cancellation Algorithm Based on Multi-Inertial Sensors for the Reduction of Motion Artifacts in Ambulatory ECGs.

Xiong Xiong,Huang Huang,Chen Chen

doi:10.3390/s20040970

Abstract

Wearable electrocardiogram (ECG) devices are universally used around the world for patients who have cardiovascular disease (CVD). At present, how to suppress motion artifacts is one of the most challenging issues in the field of physiological signal processing. In this paper, we propose an adaptive cancellation algorithm based on multi-inertial sensors to suppress motion artifacts in ambulatory ECGs. Firstly, this method collects information related to the electrode motion through multi-inertial sensors. Then, the part that is not related to the electrode motion is removed through wavelet transform, which improves the correlation of the reference input signal. In this way, the ability of the adaptive cancellation algorithm to remove motion artifacts is improved in the ambulatory ECG. Subsequent experimentation demonstrated that the wavelet adaptive cancellation algorithm based on multi-inertial sensors can effectively remove motion artifacts in ambulatory ECGs.

Highlights

An electrocardiogram records a significant amount of useful information, including human heart health status
U, V, and W represent the correlation coefficients between the angular velocity and the ECG signal, respectively, when the gyroscope is rotated around the x, y, and z axes
Motion information was collected through inertial sensors installed on different parts of the body

Summary

Introduction

An electrocardiogram records a significant amount of useful information, including human heart health status. ECG is an important basis for the diagnosis of heart disease. It can be used for diagnosing obstructive sleep apnea, evaluating therapeutic drugs, and for physiological monitoring [1]. Daily protection and long-term ECG monitoring are important methods to detect and control heart disease. Wearable ECG devices use dry electrodes that are gel-free and fabric-like, enabling long-term, dynamic, and unobstructed monitoring of ECG signals [3]. These electrodes do not make their wearers uncomfortable. One of most critical problems of wearable ECG devices is how to suppress motion artifacts. Important biosignal information can be distorted or even buried

Methods

Results

Conclusion