Article ID Journal Published Year Pages File Type
6951243 Biomedical Signal Processing and Control 2016 11 Pages PDF
Abstract
In many healthcare applications, artifacts mask or corrupt important features of Electrocardiogram (ECG) signals. In this paper we describe a revised scheme for ECG signal denoising based on a recursive filtering methodology. We suggest a suitable class of kernel functions in order to remove artifacts in the ECG signal, starting from noise frequencies in the Fourier domain. Our approach does not require high computational requirements and this feature offers the possibility of an implementation of the scheme directly on mobile computing devices. The proposed scheme allows local denoising and hence a real time visualization of the signal by means of a strategy based on boundary conditions. Experiments on real datasets have been carried out in order to test, in terms of computation and accuracy, the proposed algorithm. Finally, comparative results with other well-known denoising methods are shown.
Related Topics
Physical Sciences and Engineering Computer Science Signal Processing
Authors
, , , , ,