Automated and Robust Channel Identification Algorithm and Architecture to Solve Permutation Problem of ICA for Artifacts Removal from ECG in Remote Health Monitoring Environment

Abstract

In this paper we propose a novel channel identification algorithm for solving permutation problem introduced by Independent Component Analysis (ICA) for artifacts removal from recorded three channel ECG signals within the remote health monitoring environment. The proposed algorithm does not depend on the definition of any specific artifact which is the case with the existing approach and therefore leads to more robust and generic solution to this problem. The proposed algorithm has been validated using nine practical case studies and its robustness has been proved by comparison with the existing approach. Simulation results show that the proposed algorithm works successfully for all the nine cases whereas the existing approach fails to identify the correct channel for four cases. An architecture corresponding to the proposed algorithm is also given along with the performance analysis in terms of the hardware complexity and delay.

More information

Identifiers

Catalogue record

Export record