Designing for uncertain, asymmetric control: Interaction design for brain-computer interfaces
Designing user interfaces which can cope with unconventional control properties is challenging, and conventional interface design techniques are of little help. This paper examines how interactions can be designed to explicitly take into account the uncertainty and dynamics of control inputs. In particular, the asymmetry of feedback and control channels is highlighted as a key design constraint, which is especially obvious in current noninvasive brain-computer interfaces. Brain-computer interfaces (BCIs) are systems capable of decoding neural activity in real time, thereby allowing a computer application to be directly controlled by thought. BCIs, however have totally different signal properties than most conventional interaction devices. Bandwidth is very limited and there are compara- tively long and unpredictable delays. Such interfaces cannot simply be treated as unwieldy mice. In this respect they are an example of a growing field of sensor-based interfaces which have unorthodox control properties. As a concrete example, we present the text entry appli- cation ‘Hex-o-Spell’, controlled via motor-imagery based electroencephalography (EEG). The system utilises the high visual display bandwidth to help compensate for the limited control signals, where the timing of the state changes encodes most of the information. We present results showing the comparatively high performance of this interface, with entry rates exceeding seven characters per minute.