Infimal convolution and AM-GM majorized total variation-based integrated approach for biosignal denoising

Abstract

Biomedical measurements are generally contaminated with substantial noise from various sources, including thermal noise, interference from other physiological signals, environment, or electrode movements. Complete restoration of biosignals from noisy measurements using linear filtering techniques is not feasible owing to the spectral overlapping problem. This paper proposes an arithmetic–geometric mean inequality-based robust denoising method. The proposed method incorporates a novel convexified cost function using the concept of majorization-minimization. A two-step algorithm is derived using the forward–backward splitting technique. An optimality condition is derived to set the hyperparameters of the new algorithm. The proposed convex optimization-based method effectively denoises cardiovascular signals, including both electrocardiogram and photoplethysmography. Furthermore, the efficacy of the proposed approach is verified over different datasets. The quantitative and qualitative results obtained using the proposed method demonstrate the superiority of the proposed method in biosignal denoising concerning state-of-the-art techniques. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2023.