ABSTRACT
A brain–computer interface (BCI) is a system that provides a direct pathway between the brain and an external device, allowing people to act on the world without moving any muscle. Invasive BCI systems are those that are implanted directly into the brain of the user. This chapter describes the protocol that is used to record the neural data in the original BCI protocol and the data used to add different artifacts to it. It also describes the methodology applied to process, classify, and analyze the data. The chapter discusses the results obtained with the clean and the artifact-contaminated data sets. BCIs have a great potential both in and outside of the laboratories. The chapter analyses the rankings of artifacts in two different scenarios: one that simulates the action of training the BCI under ideal laboratory conditions and another that trains the machine using artifact-contaminated data.
