Wavelet transforms based noise reduction for body vibration signals in wireless sensor networks

In this paper we present a novel model of noise removal for the human body vibration signals in wireless sensor networks, which assumes which assumes that the noise appears not continuously or periodically but sparsely and it is the summary of some transient signals at discrete time. Furthermore, on the base of the model a new algorithm is developed which takes advantages of wavelet transforms to remove the noise by the method of processing scale functions coefficients at each level. A wavelet block is designed to implement the function of the proposed method. The results of the simulation and experiments indicate that the new algorithm has removed the noise of the signals successfully in the case of both human's one discrete action and continuous activities.