On the trade-off between compression efficiency and distortion of a new compression algorithm for multichannel EEG signals based on singular value decomposition

Authors

  • Giuseppe Campobello Department of Engineering University of Messina
  • Giovanni Gugliandolo Department of Engineering University of Messina
  • Angelica Quercia BIOMORF Department University of Messina
  • Elisa Tatti UNY School of Medicine CUNY, 160 Convent Avenue New York, NY 10031
  • Maria Felice Ghilardi UNY School of Medicine CUNY, 160 Convent Avenue New York, NY 10031
  • Giovanni Crupi BIOMORF Department University of Messina
  • Angelo Quartarone BIOMORF Department University of Messina
  • Nicola Donato Department of Engineering University of Messina

DOI:

https://doi.org/10.21014/acta_imeko.v11i2.1187

Abstract

In this article we investigate the trade-off between the compression ratio and distortion of a recently published compression technique specifically devised for multichannel electroencephalograph (EEG) signals. In our previous paper, we proved that, when singular value decomposition (SVD) is already performed for denoising or removing unwanted artifacts, it is possible to exploit the same SVD for compression purpose by achieving a compression ratio in the order of 10 and a percentage root mean square distortion in the order of 0.01 %. In this article, we successfully demonstrate how, with a negligible increase in the computational cost of the algorithm, it is possible to further improve the compression ratio by about 10 % by maintaining the same distortion level or, alternatively, to improve the compression ratio by about 50 % by still maintaining the distortion level below the 0.1 %.

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Published

2022-05-04

Issue

Vol. 11 No. 2 (2022)

Section

Research Papers

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