VHDL modelling of fixed-point DWT for the purpose of EMG signal denoising

Wavelet Transform (WT) has been widely applied in biomedical signal analysis. This paper will present the denoising method of EMG signal using WT and its model processed by VHSIC (Very High Speed Integrated Circuit) Hardware Description Language (VHDL) model of it. The principle of wavelet denoising is first to decompose the signal by performing a WT, followed by applying suitable thresholds to the detail coefficients, zeroing all coefficients below their associated thresholds, and finally to reconstruct the denoised signal based on the modified detail coefficients. Discrete Wavelet Transform (DWT) is a method that uses wavelet analyzer in which case the signal split into small pieces preserving both time and frequency properties. The Second order of Daubechies family (db2) has been used to denoise EMG signals. The simulation, synthesis and verification of the design presents a fast and reliable prototyping of DWT for denoising of EMG signals