Electrooculogram Compression based on Wavelet Packet Decomposition

Abstract

The electrooculogram (EOG) represents the electrical activity of the eye. Since most EOG-based applications need a large amount of data to be stored and transmitted, compression is required. A study on the use of discrete wavelet packet decomposition (DWPD) for compressing EOG signals is presented in this paper. The EOG signals are recorded using a commercial bioamplifier. The compression algorithm is implemented using the MATLAB software. The performance of the compression was evaluated using three parameters: compression ratio (CR), energy retention, and percent root-mean-square difference (PRD). The experimental results show that the DWPD allows for CRs of 82% while retaining almost 100% of the signal energy with a PRD of only 7%.