Context adaptive residual coding for efficient compression of MCEEG employing wave atom transforms

Abstract

Extensive use of electroencephalogram (EEG) signals in diversified fields has put in a lot of thrust in research for devices capable of operating at constrained power and storage levels. In this paper, a simple and novel method for compression of multichannel EEG (MCEEG) signal is proposed. Here, wave atom transform of MCEEG data followed by quantization, thresholding, and arithmetic coding of context adaptive residuals and threshold coefficients is performed to achieve compression with good signal quality. The proposed method has been tested on a wide range of publicly available databases and results indicate that the algorithm is able to achieve good signal compression without degrading the signal quality. The proposed system provides an average compression ratio of 14.01 with a percentage root mean square difference of 1.91% across different data sets.