Analyzing Gaming Effects on Cognitive Load Using Artificial Intelligent Tools

The paper is designed for cognitive load classification while playing games. For the processing of mundane tasks, cognitive load can be nearly equal to zero and it can increase with the complexity of the tasks. In this paper, cognitive load is measured for young individuals while playing an android game involving simple to complex brain activity. To record brain activity in terms of cognitive load during the data acquisition process, electroencephalography is used. Electroencephalogram is a type of brain-signal capturing technique, provoked by the electric field produced due to neuronal firing and captured by a sensor placed on the scalp of a subject. The captured brain signal is then processed through various steps with the ultimate aim of classifying the cognitive load of a subject into three classes: low, medium, and high while the subject engages himself in android gaming. The work can have a huge impact on society from understanding underlying game contents to provide parental controls for young individuals.