Evaluation of the index of cognitive activity (ICA) as an instrument to measure cognitive workload under differing light conditions
A straightforward and valid instrument for measuring cognitive workload would be heavily appreciated in many research areas, such as human-machine-interaction, driver behavior (e.g. automation and fatigue), usability and UI design (e.g. adaptive displays), training and education, or other areas, that are interested in the assessment of the cognitive state of a person. The Index of Cognitive Activity (ICA) is a promising but also controversially discussed instrument that could be of high relevance if it keeps its promises. The ICA is a patent from the year 2000, which claims to be an effective, light-independent recording method of mental workload. On the basis of a literature research, we carried out a lab experiment to evaluate the ICA. Participants were equipped with an Eyetracking device and worked on a mental rotation task and a Stroop task under varying light conditions. The NASA-TLX was to be answered after each test condition to evaluate the subjective workload of the participants in each condition. If the ICA is truly light-independent, the ICA should show the same mental workload for each light condition. Results show expected ICA values for the Spatial Task, but inconclusive ICA values for the Stroop Task. Possible explanations and future work is discussed.
Eye Tracking Glasses
Software
Eye Movement Analysis System in Relation to Biomechanical Perturbations
Behavior in its totality has apparent cognitive and observable findings, such as language, gesture, body, head, upper or lower limbs, facial and ocular expressions, etc., or subconscious, physiological, inappropriate such as micro-modulation of heart rate and physiological parameters, modification of ideo-motor activity etc. Analysis of eye movements is an objective way of assessing the state of concentration and attention in cognitive processes. Fundamental and applicative research in this field has highlighted a number of defining aspects of the cognitive process that relate to the different positions and movements of the eyeball. In this regard, a portable eye analysis system, correlated with biomechanical disturbances induced by the posture of the subjects was developed in the paper. The system is used to simulate synchronized postural disturbances at the same time as recording changes in human body stability and eye movement changes. The second part of the paper describes the experimental system; the sample of subjects is chosen according to the criteria established by the analysis procedure and also the recording procedures under stable and reproducible environment are developed. In the final part of the paper, results from applications and some conclusions are presented. Experimental application can determine the mode of response of eye movements in relation to the type and level of biomechanical perturbation. This response defined by the eyeball eye movement parameters can characterize the state of focus, attention or involvement by assessing behavioral coefficients. The results of the determinations are at the same time a mechanism of cognitive training and evaluation of adaptability capacity to the conditions of action of random perturbations.
Eye Tracking Glasses
Simulator
Eye movements and human-computer interaction
Gaze provides an attractive input channel for human-computer interaction because of its capability to convey the focus of interest. Gaze input allows people with severe disabilities to communicate with eyes alone. The advances in eye tracking technology and its reduced cost make it an increasingly interesting option to be added to the conventional modalities in everyday applications. For example, gaze-aware games can enhance the gaming experience by providing timely effects at the right location, knowing exactly where the player is focusing at each moment. However, using gaze both as a viewing organ as well as a control method poses some challenges. In this chapter, we will give an introduction to using gaze as an input method. We will show how to use gaze as an explicit control method and how to exploit it subtly in the background as an additional information channel. We will summarize research on the application of different types of eye movements in interaction and present research-based design guidelines for coping with typical challenges. We will also discuss the role of gaze in multimodal, pervasive and mobile interfaces and contemplate with ideas for future developments.
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Software
Eye movements in vehicle control
Measuring gaze behaviour is useful to understand the cognitive processes involved in vehicle control and to test new assistance technology. Most of the research on eye movements in vehicle control was conducted in the context of road traffic and will therefore be focused on in this chapter. In the following, we will first introduce the driving task and outline how the eye-tracking methodology can be used to get insights into the cognitive processes that guide driving behaviour. Furthermore, we will highlight important classical findings and recent developments in the field of eye movements in driving. These include eye movements during basic vehicle control tasks like steering, driving manoeuvres and detecting hazards in the road environment. Additionally, factors influencing task performance (e.g., effects of visual distraction, workload, fatigue, driving experience, and aging) that can be observed by applying the eye-tracking method will be introduced. Conducting an eye-tracking study in the driving context often takes place in complex and highly dynamic environments. Therefore, in the last part of this chapter, we will give a practical guideline of what is important in order to study eye movements in the context of vehicle control including an overview of the most commonly used parameters to describe gaze behaviour in the context of driving. We will sum up this introductory chapter with an outline for future research on the topic of eye movements in vehicle control.
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Software
Eye tracking in the wild: Piloting a real-life assessment paradigm for older adults
Previous research showed associations between personality traits and eye movements of young adults in the laboratory. However, less is known about these associations in real life and in older age. Primarily, there seems to be no paradigm to assess eye movements of older adults in real life. The present feasibility study thus aimed to test grocery shopping as a real-life assessment paradigm with older adults. Additionally, possible links between personality traits and eye movements were explored. The sample consisted of 38 older individuals (M = 72.85 years). Participants did their grocery shopping in a supermarket while wearing an eye tracker. Three key feasibility issues were examined, that is (1) wearability of the eye tracker during grocery shopping, (2) recording, and (3) evaluation of eye movements in a real-life context. Our real-life assessment paradigm showed to be feasible to implement and acceptable to older adults. This feasibility study provides specific practical recommendations which may be useful for future studies that plan to innovatively expand the traditional methods repertoire of personality science and aging research by using eye tracking in real life.
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Software
From lab-based studies to eye-tracking in virtual and real worlds: conceptual and methodological problems and solutions
Symposium Organizer: Dr. R.S. Hessels
Experimental Psychology, Helmholtz Institute, Utrecht University, the Netherlands
Summary
Wearable mobile eye trackers have great potential as they allow the measurement of eye movements during daily activities such as driving, navigating the world and doing groceries. Although mobile eye trackers have been around for some time (e.g. Land & Lee, 1994; Pelz & Canosa, 2001), developing and operating these eye trackers was generally a highly technical affair. As such, mobile eye-tracking research was not feasible for most labs. Nowadays, many mobile eye trackers are available from eye-tracking manufacturers (e.g. Tobii, Pupil labs, SMI, Ergoneers) and various implementations in virtual/augmented reality have recently been released.
The wide availability has caused the number of publications using a mobile eye tracker to increase quickly. Mobile eye tracking is now applied in vision science, educational science, developmental psychology, marketing research (using virtual and real supermarkets), clinical psychology, usability, architecture, medicine, and more. Yet, transitioning from lab-based studies where eye trackers are fixed to the world to studies where eye trackers are fixed to the head presents researchers with a number of problems. These problems range from the conceptual frameworks used in world-fixed and head-fixed eye tracking and how they relate to each other, to the lack of data quality comparisons and field tests of the different mobile eye trackers and how the gaze signal can be classified or mapped to the visual stimulus. Such problems need to be addressed in order to understand how world-fixed and head-fixed eye-tracking research can be compared and to understand the full potential and limits of what mobile eye-tracking can deliver.
In this symposium, we bring together presenting researchers from five different institutions (Lund University, Utrecht University, Clemson University, Birkbeck University of London and Rochester Institute of Technology) addressing problems and innovative solutions across the entire breadth of mobile eye-tracking research. Hessels et al. present data on the definitions of fixations and saccades held by researchers in the eye-movement field and argue how they need to be clarified in order to allow comparisons between world-fixed and head-fixed eye-tracking research. Diaz et al. introduce machine-learning techniques for classifying the gaze signal in mobile eye-tracking contexts where head and body are unrestrained. Niehorster et al. compare data quality of mobile eye trackers during natural behavior and discuss the application range of these eye trackers. Duchowski et al. introduce a method for automatically mapping gaze to faces using computer vision techniques and Haensel et al. present a novel data-driven method for statistical analysis of mobile eye-tracking data in a dyadic social interaction study. Finally, Pelz et al. employ state-of-the-art techniques to map fixations to objects of interest in the scene video and align grasp and eye-movement data in the same reference frame to investigate the guidance of eye movements during manual interaction.
The six presentations in this symposium provide both novel directions for researchers who have already been active in mobile eye-tracking research, and a comprehensive foundation for researchers considering a transition into mobile eye tracking in virtual and real worlds in the near future.
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Software
From lab-based studies to eye-tracking in virtual and real worlds: conceptual and methodological problems and solutions. Symposium 4 at the 20th European …
Wearable mobile eye trackers have great potential as they allow the measurement of eye movements during daily activities such as driving, navigating the world and doing groceries. Although mobile eye trackers have been around for some time, developing and operating these eye trackers was generally a highly technical affair. As such, mobile eye-tracking research was not feasible for most labs. Nowadays, many mobile eye trackers are available from eye-tracking manufacturers (e.g. Tobii, Pupil labs, SMI, Ergoneers) and various implementations in virtual/augmented reality have recently been released.The wide availability has caused the number of publications using a mobile eye tracker to increase quickly. Mobile eye tracking is now applied in vision science, educational science, developmental psychology, marketing research (using virtual and real supermarkets), clinical psychology, usability, architecture, medicine, and more. Yet, transitioning from lab-based studies where eye trackers are fixed to the world to studies where eye trackers are fixed to the head presents researchers with a number of problems. These problems range from the conceptual frameworks used in world-fixed and head-fixed eye tracking and how they relate to each other, to the lack of data quality comparisons and field tests of the different mobile eye trackers and how the gaze signal can be classified or mapped to the visual stimulus. Such problems need to be addressed in order to understand how world-fixed and head-fixed eye-tracking research can be compared and to understand the full potential and limits of what mobile eye-tracking can deliver. In this symposium, we bring together presenting researchers from five different institutions (Lund University, Utrecht University, Clemson University, Birkbeck University of London and Rochester Institute of Technology) addressing problems and innovative solutions across the entire breadth of mobile eye-tracking research. Hooge, presenting Hessels et al. paper, focus on the definitions of fixations and saccades held by researchers in the eyemovement field and argue how they need to be clarified in order to allow comparisons between world-fixed and head-fixed eye-tracking research. - Diaz et al. introduce machine-learning techniques for classifying the gaze signal in mobile eye-tracking contexts where head and body are unrestrained. Niehorster et al. compare data quality of mobile eye trackers during natural behavior and discuss the application range of these eye trackers. Duchowski et al. introduce a method for automatically mapping gaze to faces using computer vision techniques. Pelz et al. employ state-of-the-art techniques to map fixations to objects of interest in the scene video and align grasp and eye-movement data in the same reference frame to investigate the guidance of eye movements during manual interaction.
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Software
