Optimized Compressive Sensing Based ECG Signal Compression and Reconstruction Ishani Mishra 1,* and Sanjay Jain 2 1 Department of ECE, New Horizon College of Engineering, Bengaluru, 560103, India 2 Department of ECE, CMR Institute of Technology, Bangalore, 560037, India *Corresponding Author: Ishani Mishra. Email: ishannimishra2021@gmail.com Received: 20 August 2021; Accepted: 11 October 2021 Abstract: In wireless body sensor network (WBSN), the set of electrocardiograms (ECG) data which is collected from sensor nodes and transmitted to the server remotely supports the experts to monitor the health of a patient. However, due to the size of the ECG data, the performance of the signal compression and recon- struction is degraded. For efficient wireless transmission of ECG data, compres- sive sensing (CS) frame work plays significant role recently in WBSN. So, this work focuses to present CS for ECG signal compression and reconstruction. Although CS minimizes mean square error (MSE), compression rate and recon- struction probability of the CS is further to be improved. In this paper, we provide an efficient compressive sensing framework which strives to improve the recon- struction process, by adjusting the sensing matrix during the compression phase using the rain optimization algorithm (ROA). With the optimal sensing matrix, the compressed signal is reconstructed using Step Size optimized Sparsity Adaptive Matching Pursuit algorithm (SAMP). The results of this work demon- strate that the optimised CS framework achieves a higher compression rate and probability of reconstruction than the standard CS framework. Keywords: Wireless body sensor network (WBSN); optimized compressive sensing; step size optimized sparsity adaptive matching pursuit algorithm (SAMP); rain optimization algorithm (ROA) 1 Introduction The term “WBSN” refers to a networking technology that connects several sensor nodes within or on the human body It very well may be utilized in the use of medical care for persistent monitoring of patients [1,2]. The data is collected via a few sensor nodes that are either embedded or surface mounted on the human body and transmitted to smart devices such as cell phones or tablets. The information obtained by sensors on the smart gadget can be remotely transferred to specialists or doctors located anywhere in the globe via the Internet, who can screen, analyse, or converse with the patient remotely as the wearable sensors are attached to and move with the patients. In this way, WBSN gives mobile monitoring of patients, where patients need not be at or close to clinics for their ceaseless health observing. This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Intelligent Automation & Soft Computing DOI:10.32604/iasc.2022.022860 Article ech T Press Science