Jaffery, Z.A. and Afroz, A.K. (2010) Performance Comparison of Wavelet Threshold Estimators for ECG Signal Denoising. The IEEE International Conference on Advances in Recent Technologies in Communication and Computing (ARTCom), Kottayam, 16-17 October 2010, 248-251.

has been cited by the following article:

• TITLE: De-Noising of ECG Signals by Design of an Optimized Wavelet

  AUTHORS: Vahid Makhdoomi Kaviri, Masoud Sabaghi, Saeid Marjani

  KEYWORDS: Wavelets, De-Noising, Genetic Algorithm, ECG Signals

  JOURNAL NAME: Circuits and Systems, Vol.7 No.11, September 16, 2016

  ABSTRACT: In this paper, a different method for de-noising of ECG signals using wavelets is presented. In this strategy, we will try to design the best wavelet for de-nosing. Genetic algorithm tests wide range of quadrature filter banks and the best of them will be chosen that minimize the Signal-to-Noise Ratio (SNR). Furthermore, the wavelet function and scaling function related to these filters are reported as the best wavelet for de-noising. Simulation results for de-noising of a noisy ECG signal show that using obtained wavelet by proposed method improves the SNR of about 2.5 dB.