Analyze the beta waves of electroencephalogram signals from young musicians and non-musicians in major scale working memory task

Abstract

Electroencephalograms can record wave variations in any brain activity. Beta waves are produced when an external stimulus induces logical thinking, computation, and reasoning during consciousness. This work uses the beta wave of major scale working memory N-back tasks to analyze the differences between young musicians and non-musicians. After the feature analysis uses signal filtering, Hilbert-Huang transformation, and feature extraction methods to identify differences, k-means clustering algorithm are used to group them into different clusters. The results of feature analysis showed that beta waves significantly differ between young musicians and non-musicians from the low memory load of working memory task.

Keywords: Beta waves; Clustering analysis; Electroencephalograms; Feature extraction; Major scale; Musicians; Working memory task.