Wearable EOG goggles: Seamless sensing and context-awareness in everyday environments

Abstract

In this article we introduce the analysis of eye motion as a new input modality for activity recognition, contextawareness and mobile HCI applications. We describe a novel embedded eye tracker that, in contrast to common systems using video cameras, relies on Electrooculography (EOG). This self-contained wearable device 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. It can store data locally for long-term recordings or stream processed EOG signals to a remote device over Bluetooth. We show how challenges associated with wearability, eye motion analysis and signal artefacts caused by physical activity can be addressed with a combination of a special mechanical design, optimised algorithms for eye movement detection and adaptive signal processing. In two case studies, we demonstrate that EOG is a suitable measurement technique for the recognition of reading activity and eyebased human-computer interaction. Eventually, wearable EOG goggles may pave the way for seamless eye movement analysis in everyday environments and new forms of context-awareness not possible today.

Eye Movement Analysis for Activity Recognition Using Electrooculography

“…However, these remain expensive, with demanding video processing tasks requiring bulky auxilliary equipment. Electrooculography (EOG) -the measurement technique used in this work -is an inexpensive method for mobile eye movement recordings; it is computationally light-weight and can be implemented using wearable sensors [9]. This is crucial with a view to longterm recordings in mobile real-world settings.…”

Hybrid Brain-Computer Interface (BCI) based on the EEG and EOG signals

“…Therefore, the proposed system may not work well when the number of targets increased. This challenge will be addressed in our future work by integrating advanced acquisition equipments and signal processing algorithms of EOG to estimate precise of eye gaze direction [19,20]. Future efforts to improve the system performance will take into account the results of the previously mentioned programs, making the proposed hybrid BCI system a valuable assistive tool for disabled individuals.…”

53.1:Invited Paper:Opportunities and Hurdles for AR and VR Technology

“…Fortunately, far lower data rates are acceptable due to pupil tracking and foveated rendering. Multiple methods of pupil tracking (PT) have been constantly improving for many years for active virtual vergence correction, pupil-to-optic angle corrections, VR motion discomfort avoidance, virtual pointing, and other purposes [3,4]. The human eye only perceives about 3-5º of highest resolution at the fovea.…”