In this paper, we present a simple and efficient adaptive noise removal technique for de-noising the (ECG) signal. There are different techniques earlier used for de-noising the ECG signal ,adaptive filtration like least mean square (LMS), NLMS, BLMS , etc. In this paper we used recursive least square technique for adaptive filtration. The power line noises have been implemented according to their basic properties. After that, these noises have been mixed with ECG signal and nullify these noises using the LMS,NLMS and the RLS algorithms. Finally a performance study has been done between these algorithms based on their parameters and also discussed the effect of filter length and the corresponding signal to noise ratio. Results indicate that the noises cannot be handled by the LMS filtering whereas the RLS can handle these types of noises. Furthermore, most of the cases the RLS has achieved best effective noise cancellation performance although its computation time is slightly high. We are using the RLS Algorithm by matlab for simulation
MAHANTY, SUSHANTA and RANJAN, ALOK
"CONTROL AND ESTIMATION OF BIOLOGICAL SIGNALS (ECG) USING ADAPTIVE SYSTEM,"
International Journal of Electronics and Electical Engineering: Vol. 2
, Article 3.
Available at: https://www.interscience.in/ijeee/vol2/iss4/3