EMG Topographic Image Enhancement Using Multi Scale Filtering

Digital image enhancement is the process of adjusting image contrast to facilitate further analysis and extraction of the required features. This study presents a multi-scale, Hessian matrix based filtering, for enhancing the motor unit action potential (MUAP) propagation pattern in the multi-channel sEMG images. The proposed filter utilizes the eigenvalues of the Hessian matrix to enhance the MUAP propagation pattern, which appear as line or tubular structure in the sEMG images. The filters are tested using both simulated and experimental sEMG images. The MUAP propagation is enhanced in the images as the response of the filter is high in the direction of MUAP propagation and zero otherwise, thus suppresses the background. The resultant multi-scale filtered sEMG images provide significantly improved visualization of the MUAP propagation. This study is helpful in improving estimation of physiological and anatomical parameters from sEMG images.