Efficient EEG compression using JPEG2000 with coefficient thresholding

This paper outlines a scheme for compressing EEG signals based on the JPEG2000 image compression algorithm. Such a scheme could be used to compress signals in an ambulatory system, where low-power operation is important to conserve battery life; therefore, a high compression ratio is desirable to reduce the amount of data that needs to be transmitted. The JPEG2000 specification makes use of the wavelet transform, which can be efficiently implemented in embedded systems. In this research, the JPEG2000 standard was broken down to its core components and adapted for use on EEG signals with additional compression steps added. Variations on the compression architecture were tested to maximize compression ratio (CR) while minimizing reconstructed percentage root-mean-squared difference (PRD) and power requirements. Tests indicate that the algorithm performs well in efficiently compressing EEG data, without significant loss in signal fidelity.