A DCT-based algorithm for multi-channel near-lossless EEG compression

This article discusses the electroencephalogram (EEG) signals for the purpose of compression. The EEG signal is correlated in the time domain, a property is used to compress the EEG signal. Data compression plays an important role in reducing speed, energy transmission and the required memory for storage (reducing the cost accordingly). In this article, lossy compression based on discrete cosine transform (DCT) is used. This technique is a conservative operation and the basis of the famous format of JPEG stills. The loss of information is due to quantization. Entropy coding is also used in the compression scheme. The results found are evaluated according to two criteria: the compression ratio and reconstruction quality expressed in PRD (percent root mean-square distortion).