Brain-computer interfaces (BCIs), which use pattern-recognition methods to convert brain signals into commands suitable for the control of machines, have many applications in biomechatronics. This chapter begins by reviewing the different signal types used in BCIs (electroencephalography, electrocorticography, intracortical electrodes, and functional near-infrared spectroscopy) as well as different elicitation paradigms such as motor/mental imagery and steady-state visually evoked potentials. It then presents several possible biomechatronic applications: control of powered wheelchairs, mobile robots, artificial limbs, communication devices, BCI-triggered rehabilitation devices, adaptive automation, task difficulty adaptation, and detection of errors. The chapter concludes with a discussion of some of the challenges still faced by state-of-the-art BCIs.
