Real-Time Compression of Intra-Cerebral EEG Using Eigendecomposition with Dynamic Dictionary

Abstract

A novel technique for Intra-cerebral Electroencephalogram (iEEG) compression in real-time is proposed in this article. This technique uses eigendecomposition and dynamic dictionary update to reduce the EEG channels to only one decor related channel or eigenchannel. Experimental results show that this technique is able to provide low distortion values at very low bit rates (BRs). In addition, performance results of this method show to be better and more stable than JPEG2000. Results do not vary a lot both in time and between different patients which proves the stability of the method.