Comparison of Complexity and Regularity of ERP Recordings Between Single and Dual Tasks Using Sample Entropy Algorithm

The purpose of this study is to investigate the application of sample entropy (SampEn) measures to electrophysiological studies of single and dual tasking performance. The complexity of short-duration (~s) epochs of EEG data were analysed using SampEn along with the surrogate technique. Individual tasks consisted of an auditory discrimination task and two motor tasks of varying difficulty. Dual task conditions were combinations of one auditory and one motor task. EEG entropies were significantly lower in dual tasks compared to that in the single tasks. The results of this study have demonstrated that entropy measurements can be a useful alternative and nonlinear approach to analyzing short duration EEG signals on a time scale of seconds.