Real Time EMG Noise Cancellation from ECG Signals using Adaptive Filtering

This paper presents a quantitative study of adaptive filtering to cancel the EMG artifact from ECG signals. The proposed adaptive algorithm operates in real time; it adjusts its coefficients simultaneously with signals acquisition minimizing a cost function, the summation of weighted least square errors (LSE). The obtained results prove the success and the effectiveness of the proposed algorithm. The best ones were obtained for the forgetting factor equals to 0.99 and the regularization parameter equals to 0.02..