Approximate entropy analysis of alpha wave evoked by mental arithmetic tasks

The major purpose of this study was to explore the relationship between cognitive workload and Approximate entropy (ApEn). Mental arithmetic tasks with the different interval were assigned to the 40 subjects of different genders. ApEn method was used to analyze alpha wave at the electrode P₃, P₄, O₁ and O₂ from EEG data. It is one of nonlinear dynamics parameters to measure the complexity of sequence and quantify statistics as long as the relatively short data points are provided. Moreover, ApEn has good anti-noise and anti-jamming capability. The results show that ApEn value of about 3 / 4 the participants is higher in the 2s mental arithmetic task than in the 3s task. So it can be concluded that most of the people, whether male or female, have higher ApEn value of alpha wave at the cerebral top and occipital if their brain have more workload. It suggests the more workload increase the work complexity of the human brain. Additionally, this suggests that people should distribute reasonably workload as the human brain should not always be in a disorder conditions.