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

Thanate Angsuwatanakul, Keiji Iramina, Boonserm Kaewkamnerdpong

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

1 被引用数 (Scopus)

抄録

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.

本文言語英語
ホスト出版物のタイトルBMEiCON 2014 - 7th Biomedical Engineering International Conference
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781479968015
DOI
出版ステータス出版済み - 1 20 2015
イベント7th Biomedical Engineering International Conference, BMEiCON 2014 - Fukuoka, 日本
継続期間: 11 26 201411 28 2014

出版物シリーズ

名前BMEiCON 2014 - 7th Biomedical Engineering International Conference

その他

その他7th Biomedical Engineering International Conference, BMEiCON 2014
国/地域日本
CityFukuoka
Period11/26/1411/28/14

All Science Journal Classification (ASJC) codes

  • 生体医工学

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