Darrell S. Rudmann
ABSTRACT
1. Past research in a number of fields confirms the existence of a link between cognition and eye movement control, beyond simply a pointing relationship. This being the case, it should be possible to use eye movement recording as a basis for detecting users' cognitive states in real time. Several examples of such cognitive state detectors have been reported in the literature.2. A multi-disciplinary project is described in which the goal is to provide the computer with as much real-time information about the human state (cognitive, affective and motivational state) as possible, and to base computer actions on this information. The application area in which this is being implemented is science education, learning about gears through exploration. Two studies are reported in which participants solve simple problems of pictured gear trains while their eye movements are recorded. The first study indicates that most eye movement sequences are compatible with predictions of a simple sequential cognitive model, and it is suggested that those sequences that do not fit the model may be of particular interest in the HCI context as indicating problems or alternative mental strategies. The mental rotation of gears sometimes produces sequences of short eye movements in the direction of motion; thus, such sequences may be useful as cognitive state detecto.3. The second study tested the hypothesis that participants are thinking about the object to which their eyes are directed. In this study, the display was turned off partway through the process of solving a problem, and the participants reported what they were thinking about at that time. While in most cases the participants reported cognitive activities involving the fixated object, this was not the case on a sizeable number of trials.
- Yang, H. M., & McConkie, G. W. (1999). Reading Chinese: Some basic eye movement characteristics. In J. Wang, A. Inhoff, & H. C. Chen (Eds.) Reading Chinese Script: A Cognitive Analysis (pp. 207--222). Hillsdale, NJ: Erlbaum.Google Scholar
- Yarbus, A. L. (1967). Eye Movements and Vision. New York: Plenum Press.Google Scholar
- Findlay, J. M., & Gilchrist, I. D. (1998). Eye guidance and visual search. In G. Underwood (Ed.), Eye Guidance in Reading and Scene Perception (pp. 295-312). Amsterdam: Elsevier.Google Scholar
- Salvucci, D. D., & Anderson, J. R. (2001). Automated eye-movement protocol analysis. Human-Computer Interaction, 16,39--86. Google ScholarDigital Library
- Althoff, R., Cohen, N. J., McConkie, G. W., Wasserman, S.,Maciukenas, M., Azen, R., & Romine, L. (1998). Eye movement-based memory assessment. In W. Becker, H. Deubel, & T. Mergner (Eds.) Current Oculomotor Research: Physiological and Psychological Aspects. New York: Plenum.Google Scholar
- Jacob, R. J. K. (1991). The use of eye movements in human-computer interaction techniques: What you look at is what you get. ACM Transactions on Information Systems, 9(2), 152--169. Google ScholarDigital Library
- Edwards, G. (1998). A tool for creating eye-aware applications that adapt to changes in user behavior. Proceedings of ASSETS 98, 67--74. Google ScholarDigital Library
- Campbell, C. S. & Maglio, P. P. (2001). A robust algorithm for reading detection. In Proceedings of the ACM Workshop on Perceptual User Interfaces. Google ScholarDigital Library
- Reichle, E. D., Rayner, K., & Pollatsek, A. (in press). The E-Z Reader model of eye movement control in reading: Comparisons to other models. Behavioral and Brain Sciences.Google Scholar
- Yang, S.-N., & McConkie, G. M. (2001). Eye movements during reading: A theory of saccade initiation times. Vision Research, 41(25-26), 3567--3585.Google ScholarCross Ref
Index Terms
- Eyetracking in cognitive state detection for HCI
Recommendations
An eye tracking dataset for point of gaze detection
ETRA '12: Proceedings of the Symposium on Eye Tracking Research and ApplicationsThis paper presents a new, publicly available eye tracking dataset, aimed to be used as a benchmark for Point of Gaze (PoG) detection algorithms. The dataset consists of a set of videos recording the eye motion of human test subjects as they were ...
Pupil vs. Eyelid: Evaluating the Accuracy of Blink Detection in Pupil-based Eye Tracking Devices
AbstractSpontaneous eye blinks as a means to tap into human cognitive and affective processes have been demonstrated to offer valuable insight in various fields of application, such as human-computer-interaction and driver drowsiness detection. ...
User Eye Fatigue Detection via Eye Movement Behavior
CHI EA '15: Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing SystemsIn this study we propose and evaluate a novel approach that allows detection of physical eye fatigue. The proposed approach is based on the analysis of the recorded eye movements via what is called behavioral scores. These easy-to-compute scores can be ...
Comments