A new near-lossless EEG compression method using ANN-based reconstruction technique

Compression algorithm is an essential part of Telemedicine systems, to store and transmit large amount of medical signals. Most of existing compression methods utilize fixed transforms such as DCT and wavelet and usually cannot efficiently extract signal redundancy especially for non-stationary signals such as EEG. In this paper, we first propose learning-based adaptive transform using combination of DCT and artificial neural network (ANN) reconstruction technique. This adaptive ANN-based transform is applied to the DCT coefficients of EEG data to reduce its dimensionality and also to estimate the original DCT coefficients of EEG in the reconstruction phase.
Source: Computers in Biology and Medicine - Category: Bioinformatics Authors: Source Type: research