Analysis of electroencephalography alteration during sustained cycling exercise using power spectrum and fuzzy entropy

Szu Yu Lin, Chii Wen Jao, Po Shan Wang, Yu Te Wu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Electroencephalogram (EEG) is a common tool to study the changes in brain activity during exercise. In this study, we used recorded Electrocardiography (ECG) to define an average-to-maximal heart rate ratio (AMHRR) as a gauge of relative exercise workload, and explored how the increase of AMHRR affected the brain activity. The EEG signals were recorded from forty-four healthy subjects on four scalp sites, including C1, C2, P1, and P2 during nine minutes non-stop cycling exercise. The relationships between AMHRR and EEG power spectral or EEG fuzzy entropy (FuzzyEn) were established. Results of EEG power spectral and FuzzyEn displayed similar increasing patterns with AMHRR at all electrodes. Compared with EEG power spectral, the FuzzyEn has better specificity in selecting effective frequency bands, namely theta, alpha and beta bands. The FuzzyEn method can be applied in a wearable device for human machine interface (HMI) in monitoring the EEG during exercise in the future.

Original languageEnglish
Title of host publication2016 International Conference on Fuzzy Theory and Its Applications, iFuzzy 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781509041114
DOIs
StatePublished - 8 Aug 2017
Event2016 International Conference on Fuzzy Theory and Its Applications, iFuzzy 2016 - Taichung, Taiwan
Duration: 9 Nov 201611 Nov 2016

Publication series

Name2016 International Conference on Fuzzy Theory and Its Applications, iFuzzy 2016

Conference

Conference2016 International Conference on Fuzzy Theory and Its Applications, iFuzzy 2016
Country/TerritoryTaiwan
CityTaichung
Period9/11/1611/11/16

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