Data modelling and data processing generated by human eye movements

Data modeling and data processing are important activities in any scientific research. This research focuses on the modeling of data and processing of data generated by a saccadometer. The approach used is based on the relational data model, but the processing and storage of the data is done with client datasets. The experiments were performed with 26 randomly selected files from a total of 264 experimental sessions. The data from each experimental session was stored in three different formats, respectively text, binary and extensible markup language (XML) based. The results showed that the text format and the binary format were the most compact. Several actions related to data processing were analyzed. Based on the results obtained, it was found that the two fastest actions are respectively loading data from a binary file and storing data into a binary file. In contrast, the two slowest actions were storing the data in XML format and loading the data from a text file, respectively. Also, one of the time-consuming operations turned out to be the conversion of data from text format to binary format. Moreover, the time required to perform this action does not depend in proportion on the number of records processed.

Development of a Remote-Controlled Drone System by Using Only Eye Movements: Design of a Control Screen Considering Operability and Microsaccades

In recent years, the number of bedridden patients, including amyotrophic lateral sclerosis (ALS) patients, has been increasing with the aging of the population, owing to advances in medical and long-term care technology. Eye movements are physical functions that are relatively difficult to be affected, even if the symptoms of ALS progress. Focusing on this point, in this paper, in order to improve the quality of life (QOL) of bedridden patients, including ALS patients, we propose a drone system connected to the Internet that can be remotely controlled using only their eyes. In order to control the drone by using only their eyes, a control screen and an eye-tracking device were used in this system. By using this system, for example, the patients in New York can operate the drone in Kyoto using only their eyes, enjoy the scenery, and talk with people in Kyoto. In this drone system, since a time delay could occur depending on the Internet usage environment, agile operation is required for remotely controlling the drone. Therefore, we introduce the design of the control screen focused on remote control operability and human eye movements (microsaccades). Furthermore, considering the widespread future use of this system, it is desirable to use a commercial drone. Accordingly, we describe the design of a joystick control device to physically control the joysticks of various drone controllers. Finally, we present experimental results to verify the effectiveness of this system, including the control screen and the joystick control device.

Human visual search follows a suboptimal Bayesian strategy revealed by a spatiotemporal computational model and experiment

There is conflicting evidence regarding whether humans can make spatially optimal eye movements during visual search. Some studies have shown that humans can optimally integrate information across fixations and determine the next fixation location, however, these models have generally ignored the control of fixation duration and memory limitation, and the model results do not agree well with the details of human eye movement metrics. Here, we measured the temporal course of the human visibility map and performed a visual search experiment. We further built a continuous-time eye movement model that considers saccadic inaccuracy, saccadic bias, and memory constraints. We show that this model agrees better with the spatial and temporal properties of human eye movements and predict that humans have a memory capacity of around eight previous fixations. The model results reveal that humans employ a suboptimal eye movement strategy to find a target, which may minimize costs while still achieving sufficiently high search performance.

Dog eye movements are slower than human eye movements

Eye movement of a species reflects the visual behavior strategy that it has adapted to during its evolution. What are eye movements of domestic dogs (Canis lupus familiaris) like? Investigations of dog eye movements per se have not been done, despite the increasing number of visuo-cognitive studies in dogs using eye-tracking systems. To fill this gap, we have recorded dog eye movements using a video-based eye-tracking system, and compared the dog data to that of humans. We found dog saccades follow the systematic relationships between saccade metrics previously shown in humans and other animal species. Yet, the details of the relationships, and the quantities of each metric of dog saccades and fixations differed from those of humans. Overall, dog saccades were slower and fixations were longer than those of humans. We hope our findings contribute to existing comparative analyses of eye movement across animal species, and also to improvement of algorithms used for classifying eye movement data of dogs.

An Exploratory Study to Understand the Phenomena of Eye-Tracking Technology

Technology has played a pivotal role in revolutionizing the formative aspects of learning and teaching in the current digital age. Due to technology, there is an expectation of having customized medicine, customized interaction, and customized formative communication instead of traditional mass reporting approaches. Formative assessment within higher education teaching and learning environments are no exception to such an approach in the 21st century digital environment. Eye-tracking technology in recent years has provided an insight to understand the human eye movements and concentration patterns, which has application in education. Eye-tracking can be used to examine the processes of individuals in their learning to establish how learning contents are delivered and perceived by all involved (e.g., teaching staff, students, and markers). This chapter proposes that critical and specific information from eye-tracking software can lead to tailored educational content to accommodate, customize, and optimize the unique learning methods for an individual student as per their learning habits. This chapter describes the available eye-tracking technologies and their application in educational processes.

FRACTAL-BASED ANALYSIS OF THE INFLUENCE OF COLOR TONALITY ON HUMAN EYE MOVEMENTS

An important category of studies in vision science is related to the analysis of the influence of environmental changes on human eye movement. In this way, scientists analyze human eye movement in different conditions using different methods. An important category of works is devoted to the decoding of eye reaction to color tonality. In this research for the first time, we examined the application of fractal theory for decoding of eye reaction to variations in color intensity of visual stimuli. Three green visual stimuli with different color intensities have been applied to subjects and accordingly the fractal dimension of their eye movements has been analyzed. We also tested the eye movement in non-stimulation condition (rest). Based on the obtained results, increasing the color intensity of visual stimuli caused a lower complexity in subject’s eye movement. We also observed that eye movement is less complex in case of non-stimulation compared to different stimulation conditions. The application of fractal theory in analysis of eye movement can be extended to analyze the effect of other stimulation conditions on eye movement to investigate about the decoding behavior of human eye, which is very important in vision science.