TY  - CONF
ID  - bulling08_ubicomp
T1  - It's in {Y}our {E}yes - {T}owards {C}ontext-{A}wareness and {M}obile {HCI} {U}sing {W}earable {EOG} {G}oggles
A1  - Bulling, Andreas
A1  - Roggen, Daniel
A1  - Tröster, Gerhard
TI  - Proc. of the 10th International Conference on Ubiquitous Computing (UbiComp 2008)
Y1  - 2008
SP  - 84
EP  - 93
PB  - ACM Press
CY  - Seoul, South Korea
SN  - 978-1-60558-136-1
N1  - acceptance rate: 18.6%
M2  - doi: 10.1145/1409635.1409647
KW  - Context-awareness
KW  - Electrooculography (EOG)
KW  - Eye Gestures
KW  - Eye Tracking
KW  - Human-Computer Interaction (HCI)
KW  - Wearable Computing
N2  - 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-the-art 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 explicit eye movements for HCI, we discuss how the analysis of unconscious eye movements may eventually allow to deduce information on user activity and context not available with current sensing modalities.
ER  -