Electroencephalography (EEG) is widely used in clinical diagnosis, monitoring
and Brain - Computer Interface systems. Usually EEG signals are recorded with
several electrodes and transmitted through a communication channel for
further processing. In order to decrease communication bandwidth and
transmission time in portable or low cost devices, data compression is
required. In this paper we consider the use of fast Discrete Cosine Transform
(DCT) algorithms for lossy EEG data compression. Using this approach, the
signal is partitioned into a set of 8 samples and each set is
DCT-transformed. The least-significant transform coefficients are removed
before transmission and are filled with zeros before an inverse transform. We
conclude that this method can be used in real-time embedded systems, where
low computational complexity and high speed is required.
Fast DCT algorithms for EEG data compression in embedded systems