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. 2011:2011:6110-3.
doi: 10.1109/IEMBS.2011.6091509.

Characterization of entropy measures against data loss: application to EEG records

Eva M Cirugeda Roldán  1 , Antonio Molina-Picó, David Cuesta-Frau, Pau Miró Martínez, Sandra Oltra Crespo
Affiliations

Characterization of entropy measures against data loss: application to EEG records

Eva M Cirugeda Roldán et al. Annu Int Conf IEEE Eng Med Biol Soc. 2011.

Abstract

This study is aimed at characterizing three signal entropy measures, Approximate Entropy (ApEn), Sample Entropy (SampEn) and Multiscale Entropy (MSE) over real EEG signals when a number of samples are randomly lost due to, for example, wireless data transmission. The experimental EEG database comprises two main signal groups: control EEGs and epileptic EEGs. Results show that both SampEn and ApEn enable a clear distinction between control and epileptic signals, but SampEn shows a more robust performance over a wide range of sample loss ratios. MSE exhibits a poor behavior for ratios over a 40% of sample loss. The EEG non-stationary and random trends are kept even when a great number of samples are discarded. This behavior is similar for all the records within the same group.

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