It's in your eyes

In this work we describe the design, implementation and evaluation of a novel eye tracker for context-awareness and mobile HCI applications.In contrast to common systems using video cameras, this compact device relies on Electrooculography (EOG).It consists of goggles with dry electrodes integrated into the frame and a small pocket-worn component with a DSP for real-time EOG signal processing.The device is intended for wearable and standalone use: It can store data locally for long-term recordings or stream processed EOG signals to a remote device over Bluetooth.We describe how eye gestures can be efficiently recognised from EOG signals for HCI purposes.In an experiment conducted with 11 subjects playing a computer game we show that 8 eye gestures of varying complexity can be continuously recognised with equal performance to a state-of-theart video-based system.Physical activity leads to artefacts in the EOG signal.We describe how these artefacts can be removed using an adaptive filtering scheme and characterise this approach on a 5-subject dataset.In addition to HCI, we discuss how this paves the way for EOG-based context-awareness, and eventually to the assessment of cognitive processes.