EEG Data Compression Using Communication Techniques for PMS

Abstract

Compression of EEG (Biological) is an important issue as concern to the telemedicine area. Many of researchers have carried out the work in this domain but still the area provides an ample space for research. This research aims to develop algorithm for the compression of EEG data. In this research the constructive communication modules are used to compress the EEG data. Thirty two channels are used to load the real time EEG data. The different communication modules like transforming, filtering and coding are used to compress the data. The different evaluation performance parameters such as compression ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), signal to noise ratio (SNR), quality score etc. are obtained. Experimental results demonstrated that the quality of the constructed signal is like the original one at a low PRD, thereby obtaining better compression results compared to compression results obtained using different scheme mentioned.

Keywords: CR, PRD, PRDN, SNR, QS

Cite this Article

Taywade Seema A, Raut Rajeshree D, Dethe CG. EEG Data Compression Using Communication Techniques for PMS. Current Trends in Signal Processing. 2015; 5(3): 1-6p.