A new smoothed bootstrap resampling plan is introduced in this paper in the context of nonparametric regression smoothing. A study of the rates of convergence for this method is carried out in a similar way to that made in Cao-Abad (1991) for the normal approximation, its plug-in approach and the wild bootstrap. Finally, all these methods, used to obtain confidence intervals, are compared.