BrainTrack: A Replicable and Accessible Methodology for Customized Brain-Machine Interface Applications

This paper aims to show how a low-cost Brain-Computer Interface (BCI) device can effectively and accurately collect brain signals to control a simple machine or toy, using a versatile methodology that can adapt to different use cases. We used the EMOTIV Insight headset in conjunction with EMOTIV’s software tools to interpret brain activity and an Arduino microcontroller to handle interfacing between the computer and the controlled device. This study evaluates the feasibility of moving a car on a slot car track using the focus levels of the user as a reference. Comparing the concentration levels achieved while completing a logic-based puzzle with those reached when focusing on the car suggests the viability of this approach for the task since users can effectively and consciously control their attention level. This approach offers flexibility to adapt a wide range of appliances or toys without reliance on the manufacturer to provide accessibility, offering to people with severe physical disabilities new opportunities to interact with the world. The proposed methodology allows to conduct testing inexpensively and effectively, helping discern the best approach for a customized product before manufacturing it.