Individualization of a vectorcardiographic model by a particle swarm optimization

An efficient ECG signals denoising technique based on the combination of particle swarm optimisation and wavelet transform

“…In this paper, we propose utilising particle swarm optimisation (PSO), which has gained widespread usage and achieved notable success in various engineering fields [ [44] , [45] , [46] ], to optimise discrete wavelet transform (DWT) parameters for efficient ECG signal denoising in both PLI and AWGN scenarios. Additionally, we have optimised all five DWT filter parameters: namely, the wavelet filter, the decomposed level, the scaling factor, the threshold method, and the rescaling technique.…”