Wireless sensor networks, with their low cost, small size, low energy consumption expanding their use in home automation and environmental monitoring systems. With the help of these benefits there has been an increasing demand on wireless patient monitoring systems recently. One of the important parts of patient monitoring systems is ECG measurement which requires high resolution sampling and high data rates. That leads a ceartain need of a low loss and low complexity data compression for systems like Zigbee and Bluetooth which can not provide high data rates and high computing power. In this study two low complexity lossless and low-loss data compression algorithms are presented being able to use in wireless sensor networks. First algorithm implements a shift values for the greater inputs with a pre-selected shifting steps to lower value. The second method implements a low-loss logaritmic scaling to samples that expressed by more than a byte for reducing the content to 1 byte like first algortihm. Thus, a significant data reduction has been made for a low data rate wireless communications, i.e. Bluetooth and ZigBee, which helps to reduce the latency. Proposed techniques keep the sensitive portion of the data untouched, as in ECG signals, and can be implemented by a very low profile microprocessor.