Robust channel identification scheme: solving permutation indeterminacy of ICA for artifacts removal from ECG.

In this paper we propose a novel channel identification scheme for solving permutation indeterminacy introduced by Independent Component Analysis (ICA) for artifacts removal from recorded three channel ECG signals within the remote health monitoring environment. The proposed scheme 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 scheme 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 scheme works successfully for all the nine cases whereas the existing approach fails to identify the correct channel for four cases.