Optimized Compressed ECG data Using PSO over Zigbee module Rajeev Kumar1, Tony Singla2 1Faculty of Information Technology, DAV Institute of Engineering and Technology, India 2Research Scholar of Computer Science and Engineering, DAV Institute of Engineering and Technology, India Abstract: Survey pretention puts the concern over the health monitoring areas; cardiovascular diseases rise up from the bottom and marks remarkable heights in death claiming calendar of India. Standard Electrocardiogram (ECG) Tracking instruments are huge to carry away over the remote areas and will not report change in the Heart Rhythm under hours of surveillance. Holter is the compact instrument meant for collecting ECG of a patient without a pause while the patient is on the go of their daily activities, local process of ECG evaluation is transformed into a remote process. Holter works on battery for 24 or 48 hours continuously without any angle of transmission but when allowed to transmit battery power dies soon, for this purpose some energy saving techniques are to be applied. In this paper we have proposed a Wavelet based Compression Technique (DWT), followed by Optimization under Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). Compressed and Optimized ECG data has been transferred over Zigbee IEEE 802.15.4 environment with the intention of saving energy implicating it on a hardware chip. Transferred data will be available to the Doctor for on time treatment and further examination and storage. Embedded prior techniques in Holter can enhance its life, with fact of sending crucial data. Keywords: Electrocardiogram (ECG), Wireless Sensor Network (WSN) , Discrete Wavelet Transform(DWT), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), Zigbee (802.15.4). 1. Introduction Present time reveals the truth that there is a raise in the aging population, busy world and life taking diseases [1]. Ongoing era demands the early detection and prevention of death threatening diseases [2], out of a huge number here the main focus is on cardiovascular diseases [3,4]. Cardiovascular diseases