The Design of an Algorithmic Modal Music Platform for Eliciting and Detecting Emotion

In the past decade, the usage of brain-computer interfaces (BCI) in affective computing applications has received much attention within human-computer interaction (HCI) applications. Generally, affective brain-computer interfaces are utilized in user experience evaluation, intelligent tutoring systems, and emotional state assessment. In addition, BCI technology has yielded promising results in various contexts such as clinical applications, like P300 spellers, mouse pointers, and wheelchair controllers, as well as in artistic and entertainment-focused applications such as gaming and music composition. The present work describes the design of a platform for eliciting emotion through modal music that has been algorithmically generated and comparing BCI data to self-reported emotional data to validate the detection of emotion. The successful realization of such a system will validate the analysis of BCI-detected emotion. In addition, the system will create new avenues of musical and emotional expression for people with disabilities that hinder this articulation.