Geodesic
Fast DCT Algorithms for EEG Data Compression in Embedded Systems
Computer Science and Information Systems, Tome 12 (2015) no. 1.

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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.
Keywords: Fast DCT, data compression, electroencephalography 
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     author = {Darius Birvinskas and Vacius Jusas and Ignas Martisius and Robertas Damasevicius},
     title = {Fast {DCT} {Algorithms} for {EEG} {Data} {Compression} in {Embedded} {Systems}},
     journal = {Computer Science and Information Systems},
     publisher = {mathdoc},
     volume = {12},
     number = {1},
     year = {2015},
     url = {http://geodesic.mathdoc.fr/item/CSIS_2015_12_1_a3/}
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Darius Birvinskas; Vacius Jusas; Ignas Martisius; Robertas Damasevicius. Fast DCT Algorithms for EEG Data Compression in Embedded Systems. Computer Science and Information Systems, Tome 12 (2015) no. 1. http://geodesic.mathdoc.fr/item/CSIS_2015_12_1_a3/