Exploring task design for cognitive commands and prerequisites of accessibility with a visual Imagery task for spontaneous EEG

I have explored skills required for end-users to operate a BCI communication system, attempted to define optimal cognitive commands for task design with Stimulus-Response compatibility, and discussed how hardware and system design may support accessibility. I have performed experiments with an Emotiv EEG headset and a game interface to find and the participants have reported perceived Workload with a NASA Tlx form. I have assessed the effectiveness and user experience of spontaneous EEG, by testing training data with different cognitive tasks and compared them with number of classifications per session, and the score achieved. There are benefits in user motivation and workload if we can adjust tasks to skill level and customize stepwise skill acquisition to the individual user. I have hypothesised that a trade-off in dataset similarity may outweigh the benefits of a more accessible workflow. There is no significant evidence of a difference in tested efficiency or accuracy between using visual imagery and visual perception as training data with visual imagery gameplay task. There is no significant evidence of a difference in perceived workload between playing with different sets of training data. I discuss how further development in machine learning models may fascilitate even further to a desired accessibility with cognitive command