Context-aware brain-computer interfaces

Developments in neuroscience, signal processing and machine learning are enabling device control using our brain activity. Specifically, current technology allows us to record braingenerated signals in real time, infer the human intention and translate it into control commands for external devices. These brain-computer interfaces (BCIs) can currently control virtual keyboards, games, smart wheelchairs and mobile robots.1 Most commonly, BCI systems are based on electrical brain activity recorded on the scalp (using electroencephalograms: EEGs). Machine-learning techniques help to classify these signals into pre-defined patterns of activity associated with particular intentions (e.g., imagining moving one’s left hand will lead to device motion toward the left). BCI applications have traditionally focussed on subjects suffering frommotor handicaps (caused by, for instance, spinal-cord injury, degenerative diseases or lockedin syndrome). Their predominant aim has been restoration or substitution of communication and/or motor capabilities, although recent developments have also explored their use in healthy subjects in applications ranging from games2 to image browsing3 and space-system applications.4 However, despite their impressive achievements, BCI applications are strongly limited by their low throughput and the small number of commands they can deliver. Designing context-aware interfaces has been proposed as a way to cope with these limitations. Using this approach, the interface collects information about the state of the device, as well as its environment, and combines this with the commands it has decoded from brain activity (see Figure 1). This enables the performance of complex tasks with a reduced number of mental commands (typically two or three) and using the latter to signal high-level instructions while smart devices take care of low-level controlsignals. For instance, we have shown that noninvasive BCIs can be used for real-time control of an intelligent wheelchair in realistic conditions.5 In this application, BCI commands are limited to general directions of movement (i.e., move forward, turn left Figure 1. Context-aware brain-computer interface (BCI). The traditional BCI control loop is enriched by the addition of contextual information describing the environment and the user’s cognitive state. EEG: Electroencephalogram.