Brain-Computer Interfaces (BCIs) are systems that can translate brain activity patterns into messages or commands for an interactive application. As such the technology used to design them, and in particular to design passive BCIs which are a new means to perform mental state monitoring, can greatly benefit the neuroergonomics field. Therefore, this chapter describes the classical structure of the brain signal processing chain employed in BCIs, notably presenting the typically used preprocessing (spatial and spectral filtering, artefact removal), feature extraction and classification algorithms. It also gives examples of the use of BCI technology for neuroergonomics applications, either offline for evaluation purposes (e.g. cockpit design or stereoscopic displays’ assessment), or online for adaptation purposes (e.g. video game difficulty level or air traffic controller display adaptation).