Analysis of Electroencephalography Alteration During Sustained Cycling Exercise Using Power Spectrum and Fuzzy Entropy

An electroencephalogram (EEG) is commonly used to study changes in brain activity during exercise. In this study, we used recorded electrocardiography to define the average-to-maximal heart rate ratio (AMHRR) as a gauge of relative exercise workload, and explored how an increase in the AMHRR affected brain activity. EEG signals were recorded from 44 healthy subjects at four scalp sites (i.e., C1, C2, P1, and P2) during 9-min nonstop cycling exercise. The relationships among the AMHRR, EEG spectral power, and EEG fuzzy entropy (FuzzyEn) were established. The EEG spectral power and FuzzyEn results displayed similarly increasing patterns with the AMHRR at all electrodes. However, FuzzyEn exhibited superior specificity in selecting effective frequency bands (i.e., theta, alpha, and beta). The FuzzyEn method can be applied in a wearable device for a human machine interface, which can monitor the EEG during exercise.