Using DWT Lifting Scheme for Lossless Data Compression in Wireless Body Sensor Networks

Abstract

Recently, interest in Wireless Body Sensor Networks composed by low-power devices which are placed in, on or around the body has been increased. Wireless Body Sensor Networks open up tremendous healthcare and wellness applications such as continuous monitoring of a patient's vital signs. One of the fundamental challenges in Wireless Body Sensor Networks is energy consumption due to wireless transmission of collected data. In this paper, we aim to extend the life-time of battery-powered biosensors by applying a data reduction technique that works efficiently under constrained processing, storage, and energy resource conditions. The presented technique is a lossless transform-based compression technique based on the Discrete Wavelet Transform using the lifting scheme extended with Lagrange polynomial interpolation. To evaluate our approach, we have run multiple series of simulations on real sensor data. The results show that our proposed method reduces the amount of data by up to 90% without losing any information.