Multi-scale sample entropy as a feature for working memory study

Conference proceedings article

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Publication Details

Author list: Angsuwatanakul T., Iramina K., Kaewkamnerdpong B.

Publisher: Hindawi

Publication year: 2015

ISBN: 9781479968015

ISSN: 0146-9428

eISSN: 1745-4557

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923064449&doi=10.1109%2fBMEiCON.2014.7017446&partnerID=40&md5=2e302fe9d73a43e055170256be0a5def

Languages: English-Great Britain (EN-GB)

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Abstract

Toward the understanding of how human brains work so that we could manage to effectively improve the conditions of neurological disorders or even enhance the cognitive performance, working memory study is of interest. Multi-scale sample entropy has been used to analyze the complexity of biomedical data. This study aims to investigate the potential of using multi-scale sample entropy as a feature for characterizing memory. We applied complexity analysis on EEG data recorded during a cognitive experiment targeting working memory through visual stimuli. The results revealed the distinctive sample entropy for various memory cases in prefrontal area. This indicated the potential of using multi-scale sample entropy for characterizing memory. ฉ 2014 IEEE.

Keywords

electroencephalography (EEG), multi-scale sample entropy (MSE), Neuroimaging, neuroinformatics, Working memory