Researchers have begun to investigate the relationship between eye movement characteristics of gaze patterns and cognitive abilities, and have attempted to use eye-tracking technology as a new method to evaluate cognitive abilities. Traditional eye movement analysis methods typically separate spatial and temporal information of eye movements, mostly analyze averaged data, and consider individual differences as noise. In addition, current eye movement studies on gaze patterns mostly involve adults, while research on infants and toddlers is limited with small sample sizes and narrow age ranges. It is still unknown whether the conclusions drawn from adult-based research can be applied to children. Consequently, eye movement research on gaze patterns in children is necessary. To address the concerns stated above, this study used the Hidden Markov machine learning method to model gaze patterns of 330 children aged 1-6 years while observing faces freely, and analyzed characteristics of eye movement gaze patterns. Additionally, we analyzed the correlation between gaze patterns of 31 toddlers aged 1-3 years and 37 preschoolers aged 4-6 years, and the different dimensions of cognitive abilities. The findings indicated that children exhibited holistic and analytic gaze patterns while observing different faces freely. More children adopted a holistic gaze pattern, and there were age-specific gaze pattern characteristics and regularities. Gaze patterns of toddlers may be correlated with their adaptive abilities and gaze patterns of preschoolers may be correlated with their visual space abilities. Specifically, toddlers aged 1-3 years showed a moderate negative correlation between the H-A scale and the adaptive dimension, while preschoolers aged 4-6 years showed a low negative correlation between the H-A scale and the visual space dimension. This study may provide new insights into the characteristics of children's eye-movement gaze patterns during face observation, and potentially offer objective evidence for future research aimed at promoting the use of eye-tracking technology in the assessment of toddlers' adaptive abilities and preschoolers' visual space abilities in the field of face perception.
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http://dx.doi.org/10.3389/fnhum.2023.1220178 | DOI Listing |
Sensors (Basel)
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Department of Civil Engineering and Architecture, University of Catania, 64 Santa Sofia Street, 95123 Catania, Italy.
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Computer Science Department, Yarmouk University, Irbid 21163, Jordan.
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View Article and Find Full Text PDFAnimals (Basel)
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Havemeyer Equine Behavior Laboratory, Section of Reproduction and Behavior, Department of Clinical Studies, University of Pennsylvania School of Veterinary Medicine, New Bolton Center, Kennett Square, PA 19348, USA.
Gastric ulcer disease and other potentially painful gastric conditions are among the most common afflictions adversely affecting the welfare of domestic equids. A large percentage of affected animals may not display the classic signs of gastric disease, such as unexplained weight loss, poor hair coat, and inappetence until the disease becomes severe. As a clinical service within our equine referral hospital, we routinely evaluate 24-h video recorded samples of horses to assist clinicians in identifying subtle discomfort and potential sources or to scan for infrequent neurologic or cardiac-related behavioral events.
View Article and Find Full Text PDFPLoS One
January 2025
Faculty of Philosophy, Philosophy of Science and the Study of Religion, Ludwig Maximilian University of Munich, München, Germany.
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View Article and Find Full Text PDFTraffic Inj Prev
January 2025
National Key Laboratory of Human Factors Engineering, China Astronaut Research and Training Centre, Beijing, China.
Objective: Attention forms the foundation for the formation of situation awareness. Low situation awareness can lead to driving performance decline, which can be dangerous in driving. The goal of this study is to investigate how different types of pre-takeover tasks, involving cognitive, visual and physical resources engagement, as well as individual attentional function, affect driver's attention restoration in conditionally automated driving.
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