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         "type" : "Publication",
         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/24f6c9958981e8685998dbb12a6ebfe32/hcics",         
         "tags" : [
            "(EOG),","(HCI),","Computing","Context-awareness,","Electrooculography","Eye","Gestures,","Human-Computer","Interaction","Tracking,","Wearable","hcics","vis"
         ],
         
         "intraHash" : "4f6c9958981e8685998dbb12a6ebfe32",
         "interHash" : "bb44e9ef1e678d0cb7258dde2d2abbdf",
         "label" : "It's in Your Eyes - Towards Context-Awareness and Mobile HCI Using Wearable EOG Goggles",
         "user" : "hcics",
         "description" : "",
         "date" : "2024-07-11 10:05:52",
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         "pub-type": "inproceedings",
         "booktitle": "Proc. ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp)",
         "year": "2008", 
         "url": "", 
         
         "author": [ 
            "Andreas Bulling","Daniel Roggen","Gerhard Tröster"
         ],
         "authors": [
         	
            	{"first" : "Andreas",	"last" : "Bulling"},
            	{"first" : "Daniel",	"last" : "Roggen"},
            	{"first" : "Gerhard",	"last" : "Tröster"}
         ],
         "pages": "84-93","abstract": "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.",
         "doi" : "10.1145/1409635.1409647",
         
         "bibtexKey": "bulling08_ubicomp"

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         "id"   : "https://puma.ub.uni-stuttgart.de/bibtex/26ec56d592f782c80d5a3ccde317895fc/hcics",         
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            "(EOG),","(HCI),","Computing","Context-awareness,","Electrooculography","Eye","Gestures,","Human-Computer","Interaction","Tracking,","Wearable","hcics","vis"
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         "intraHash" : "6ec56d592f782c80d5a3ccde317895fc",
         "interHash" : "e687f966a40a4b0ec3b8b18cf47cf752",
         "label" : "Wearable EOG Goggles: Eye-Based Interaction in Everyday Environments",
         "user" : "hcics",
         "description" : "",
         "date" : "2024-07-11 10:05:52",
         "changeDate" : "2024-07-11 10:11:36",
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         "pub-type": "inproceedings",
         "booktitle": "Ext. Abstr. ACM SIGCHI Conference on Human Factors in Computing Systems (CHI)",
         "year": "2009", 
         "url": "", 
         
         "author": [ 
            "Andreas Bulling","Daniel Roggen","Gerhard Tröster"
         ],
         "authors": [
         	
            	{"first" : "Andreas",	"last" : "Bulling"},
            	{"first" : "Daniel",	"last" : "Roggen"},
            	{"first" : "Gerhard",	"last" : "Tröster"}
         ],
         "pages": "3259-3264","abstract": "In this paper, we present an embedded eye tracker for context-awareness and eye-based human-computer interaction â\u20AC\u201C the wearable EOG goggles. In contrast to common systems using video, this unobtrusive device relies on Electrooculography (EOG). It consists of goggles with dry electrodes integrated into the frame and a small pocket-worn component with a powerful microcontroller for EOG signal processing. Using this lightweight system, sequences of eye movements, so-called eye gestures, can be efficiently recognised from EOG signals in real-time for HCI purposes. The device is self-contained solution and allows for seamless eye motion sensing, context-recognition and eye-based interaction in everyday environments.",
         "doi" : "10.1145/1520340.1520468",
         
         "bibtexKey": "bulling09_chi"

      }
	  
   ]
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