Not All Created Equal: Individual-Technology Fit of Brain-Computer Interfaces

Abstract

This work presents a model stemming from literature on task-technology fit that seeks to match individual user characteristics and features of brain-computer interface technologies with performance to expedite the technology-fit process. The individual-technology fit model is tested with a brain-computer interface based on a control signal called the mu rhythm that is recorded from the motor cortex region. Characteristics from eighty total participants are tested across two different sessions. Performance is measured as a person's ability to modulate his/her mu rhythm. It appears that the version of software used in recording and interpreting EEGs, instrument playing, being on affective drugs, a person's sex, and age all play key roles in predicting mu rhythm modulation.