Publications
Explore a collection of publications and projects, from diverse fields, that cite Pupil Labs and use Pupil Labs eye tracking hardware and software in their research. You can also find this collection on Zotero.
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0-0 of 560 publications
Wine label design proposals: an eye-tracking study to analyze consumers’ visual attention and preferences
International Journal of Wine Business Research
Purpose
The main purpose of this study is to analyze how consumers’ visual attention to wine label design correlates with their preferences. Accordingly, this study uses quantitative eye-tracking metrics to understand which design proposal has greater visual salience. A more specific objective was to assess which design proposal was preferred to be marketed.
Design/methodology/approach
The experiment involved evaluating of three different labeling proposals of an Italian winery. Infrared eye-tracking was used to measure implicit eye movements on the three bottles displayed, simultaneously, on a computer screen. A generalized linear model was used to test how consumers' visual attention to wine label design correlated with their preferences.
Findings
The design proposals were evaluated significantly differently, with one set being preferred. In general, a strong positive relationship was found between pausing to peruse a specific design proposal and making an explicit choice of the same bottle.
Research limitations/implications
The main limitation of the experiment concerns the sample interviewed. As the sample is homogeneous, the results may not be generalizable to other segments. Furthermore, the addition of electroencephalographic devices that monitor brain activity could provide crucial information for understanding consumer behavior during the purchase decision-making process.
Practical implications
Eye-tracking methods could be useful for designers and wine producers during the evaluation process of design projects.
Originality/value
The use of eye-tracking for evaluating design proposals before placing a product on the market is relatively novel. This method provides objective, quantitative and predictive information on consumer preferences contributing guidelines to designers and marketers during the product conception phase.
Accessible Dyslexia Detection with Real-Time Reading Feedback through Robust Interpretable Eye-Tracking Features
Brain Sciences
Developing reliable, quantifiable, and accessible metrics for dyslexia diagnosis and tracking represents an important goal, considering the widespread nature of dyslexia and its negative impact on education and quality of life. In this study, we observe eye-tracking data from 15 dyslexic and 15 neurotypical Serbian school-age children who read text segments presented on different color configurations. Two new eye-tracking features were introduced that quantify the amount of spatial complexity of the subject’s gaze through time and inherently provide information regarding the locations in the text in which the subject struggled the most. The features were extracted from the raw eye-tracking data (x, y coordinates), from the original data gathered at 60 Hz, and from the downsampled data at 30 Hz, examining the compatibility of features with low-cost or custom-made eye-trackers. The features were used as inputs to machine learning algorithms, and the best-obtained accuracy was 88.9% for 60 Hz and 87.8% for 30 Hz. The features were also used to analyze the influence of background/overlay color on the quality of reading, and it was shown that the introduced features separate the dyslexic and control groups regardless of the background/overlay color. The colors can, however, influence each subject differently, which implies that an individualistic approach would be necessary to obtain the best therapeutic results. The performed study shows promise in dyslexia detection and evaluation, as the proposed features can be implemented in real time as feedback during reading and show effectiveness at detecting dyslexia with data obtained using a lower sampling rate.
A wearable platform for closed-loop stimulation and recording of single-neuron and local field potential activity in freely moving humans
Nature Neuroscience
Abstract
Advances in technologies that can record and stimulate deep brain activity in humans have led to impactful discoveries within the field of neuroscience and contributed to the development of novel therapies for neurological and psychiatric disorders. Further progress, however, has been hindered by device limitations in that recording of single-neuron activity during freely moving behaviors in humans has not been possible. Additionally, implantable neurostimulation devices, currently approved for human use, have limited stimulation programmability and restricted full-duplex bidirectional capability. In this study, we developed a wearable bidirectional closed-loop neuromodulation system (Neuro-stack) and used it to record single-neuron and local field potential activity during stationary and ambulatory behavior in humans. Together with a highly flexible and customizable stimulation capability, the Neuro-stack provides an opportunity to investigate the neurophysiological basis of disease, develop improved responsive neuromodulation therapies, explore brain function during naturalistic behaviors in humans and, consequently, bridge decades of neuroscientific findings across species.
Assessing the allocation of attention during visual search using digit-tracking, a calibration-free alternative to eye tracking
Scientific Reports
Abstract
Digit-tracking, a simple, calibration-free technique, has proven to be a good alternative to eye tracking in vision science. Participants view stimuli superimposed by Gaussian blur on a touchscreen interface and slide a finger across the display to locally sharpen an area the size of the foveal region just at the finger's position. Finger movements are recorded as an indicator of eye movements and attentional focus. Because of its simplicity and portability, this system has many potential applications in basic and applied research. Here we used digit-tracking to investigate visual search and replicated several known effects observed using different types of search arrays. Exploration patterns measured with digit-tracking during visual search of natural scenes were comparable to those previously reported for eye-tracking and constrained by similar saliency. Therefore, our results provide further evidence for the validity and relevance of digit-tracking for basic and applied research on vision and attention.
Investigating Visual Perception Impairments through Serious Games and Eye Tracking to Anticipate Handwriting Difficulties
Sensors
Dysgraphia is a learning disability that causes handwritten production below expectations. Its diagnosis is delayed until the completion of handwriting development. To allow a preventive training program, abilities not directly related to handwriting should be evaluated, and one of them is visual perception. To investigate the role of visual perception in handwriting skills, we gamified standard clinical visual perception tests to be played while wearing an eye tracker at three difficulty levels. Then, we identified children at risk of dysgraphia through the means of a handwriting speed test. Five machine learning models were constructed to predict if the child was at risk, using the CatBoost algorithm with Nested Cross-Validation, with combinations of game performance, eye-tracking, and drawing data as predictors. A total of 53 children participated in the study. The machine learning models obtained good results, particularly with game performances as predictors (F1 score: 0.77 train, 0.71 test). SHAP explainer was used to identify the most impactful features. The game reached an excellent usability score (89.4 ± 9.6). These results are promising to suggest a new tool for dysgraphia early screening based on visual perception skills.
Using Task-Evoked Pupillary Response to Predict Clinical Performance during a Simulation Training
Healthcare
Training in healthcare skills can be affected by trainees’ workload when completing a task. Due to cognitive processing demands being negatively correlated to clinical performance, assessing mental workload through objective measures is crucial. This study aimed to investigate task-evoked changes in pupil size as reliable markers of mental workload and clinical performance. A sample of 49 nursing students participated in a cardiac arrest simulation-based practice. Measurements of cognitive demands (NASA-Task Load Index), physiological parameters (blood pressure, oxygen saturation, and heart rate), and pupil responses (minimum, maximum, and difference diameters) throughout revealed statistically significant differences according to performance scores. The analysis of a multiple regression model produced a statistically significant pattern between pupil diameter differences and heart rate, systolic blood pressure, workload, and performance (R2 = 0.280; F (6, 41) = 2.660; p < 0.028; d = 2.042). Findings suggest that pupil variations are promising markers to complement physiological metrics for predicting mental workload and clinical performance in medical practice.
Theta and alpha EEG oscillations reflect sleep need — except during the wake maintenance zone
Neuroscience
ABSTRACT
Increasing time spent awake results in accumulated sleep need, a process known as sleep homeostasis. Sleep homeostasis combines with a 24 h circadian rhythm to determine when and for how long we sleep. Both sleep homeostasis and the circadian rhythm substantially affect spectral power of the wake electroencephalogram (EEG), but not in ways predicted by current models. Specifically, these models hypothesize that time spent awake increases neuronal synaptic strength, which increases synchronization and should therefore increase oscillatory activity. However, the dominant wake EEG oscillations, measured as theta (4-8 Hz) and alpha power (8-12 Hz), do not follow the predicted buildup in homeostatic sleep pressure with time awake. This is due to a limitation of spectral power analysis, which does not distinguish between changes in the amplitude of oscillations from changes in the quantity of oscillations present in the signal. We wished to determine whether the amplitudes of EEG oscillations would specifically reflect homeostatic sleep pressure, independently from changes in quantity. We collected data from 18 young healthy adults during a 4-h sleep / 24-h extended wake paradigm. We indeed found that theta and alpha oscillation amplitudes reflect homeostatic sleep pressure, increasing along a saturating exponential function with time awake. Instead, theta quantities increased linearly with time awake, and alpha quantities decreased. Notably, theta and alpha amplitudes temporarily decreased during the wake maintenance zone (WMZ), a 3-4 h time window just before bedtime when it is difficult to fall asleep. Using pupillometry, we also found that mean pupil diameter increased during this window, while variance decreased. These results suggest that the WMZ is dependent on an alerting signal from the ascending arousal system. The WMZ therefore counteracts the observed build-up in homeostatic sleep pressure reflected in EEG amplitudes by temporarily desynchronizing cortical activity.