Effects of Learning Task Difficulties on the Prefrontal Brain Area
This study addresses the issue of estimating mental efforts during a learning task based on brain signal measurements. The aim of this study is to describe how a Brain Computer Interface (BCI) can be used as a direct communication tool between the human brain and a machine in the context of learning. Such devices are based on analyzing the electrical brain activity measurements using different brain exploration technics. In this study we describe an offline method to highlight effects of changing difficulty levels of a learning task on the prefrontal brain area status. Based on a single ElectroEncephaloGraphic (EEG) channel and using the Fisher Snedecor test our proposed algorithm describes changes of Delta (0.5 3Hz) Theta (4 7Hz) and Alpha (8 11Hz) band powers. By using the Kappa coefficients, to assess the agreement rate between the algorithm decisions and those made by an expert, experimental results show a rate of 62% of agreement. This reflects the efficiency of the proposed method in distinguishing effects of difficulty levels of a learning task on the prefrontal brain area.