Eye Movement Characteristics Research Articles

Analysis on the characteristics of eye movement and the evaluation of psychological perception for forest waterscape space

For landscape architects, how to provide a highly quality forest landscape for visitors has always been an important topic. This study based on the results of previous field observation, combined with eye tracking technology and psychological perception questionnaire, and used the Wilcoxon rank sum test, T test and Spearman’s rho correlation analysis in SPSS 23.0 to statistically analyze the data. The main purpose is to clarify the relationship between visual behavior characteristics and psychological perception evaluation of the forest waterscape space where tourists have more behavioral evaluations during forest walk. Main results are as follows: 1. There are differences eye movement behaviors of different types of forest waterscape space, especially in the visual span; 2. There are significant differences visitor’s psychological evaluation of different types of forest waterscape in five indices, which in whether the landscape content is changing, whether the color is rich, whether the color is bright, whether the space is open and whether you can see the distant landscape; 3. There is a correlation between human eye movement behavior and psychological perception evaluation in different types of forest waterscape spaces. The scenes with a large number of fixations also have higher satisfaction, and fixations count have positively correlated with the spatial perception evaluation results, which including plant diversity, landscape richness, permeability and the layering. That is to say, richness of landscape elements and color, permeability of the space and the regularity of the forest waterscape space affect the participants’ eye movement observation mode. Through the above analysis, we suggest that in the planning and design of forest waterscape space should be considerate the characteristics of different landscape elements, meanwhile we should pay attention to the interspersion of appropriate heterogeneous landscape space.

Waveform characterisation and comparison of nystagmus eye-tracking signals

Objective. Pathological nystagmus is a symptom of oculomotor disease where the eyes oscillate involuntarily. The underlying cause of the nystagmus and the characteristics of the oscillatory eye movements are patient specific. An important part of clinical assessment in nystagmus patients is therefore to characterise different recorded eye-tracking signals, i.e. waveforms. Approach. A method for characterisation of the nystagmus waveform morphology is proposed. The method extracts local morphologic characteristics based on a sinusoidal model, and clusters these into a description of the complete signal. The clusters are used to characterise and compare recordings within and between patients and tasks. New metrics are proposed that can measure waveform similarity at different scales; from short signal segments up to entire signals, both within and between patients. Main results. The results show that the proposed method robustly can find the most prominent nystagmus waveforms in a recording. The method accurately identifies different eye movement patterns within and between patients and across different tasks. Significance. In conclusion, by allowing characterisation and comparison of nystagmus waveform patterns, the proposed method opens up for investigation and identification of the underlying condition in the individual patient, and for quantifying eye movements during tasks.

Effectiveness of viewer’s exeperience for features of eye movement in viewing football games

Effectiveness of viewer’s exeperience for features of eye movement in viewing football games

Safety Assessment of Exit Advance Guide Signs in Mountainous Highway Tunnel Based on Eye-Tracking Technology

Exit Advance Guide Signs play an important role in driving safety on highway tunnels. With the increase of mountain highway in recent 10 years, how to set exit advance guide signs inside the mountain highway tunnels become a new problem in China. This paper evaluates the effects of setting schemes of Exit Advance Guide Signs in mountain tunnels through simulation experiments. Specially, exit advance guide signs in the mountainous highway tunnel were divided into location sign and distance sign. Six schemes of different height, width and spacing were tested, in which the distance sign was on the left or right wall of the tunnel, and the vehicle was on the left lane. A Markov chain was used to analyze the driver's eye movement characteristics to evaluate the effect of separate guide signs. The results were as follows: if the distance sign was set on the left wall, the scheme 4 where height, width and spacing of 1.5m was the best choice, because the change rate of the driver's pupil area was higher than the threshold, attention to distance signs increased to 10.42%, and dashboard gaze also increased. These characteristics show that the traffic sign setting effect was obvious, and didn't affect the driver's driving safety; if the distance sign was set on the right wall, the scheme 6 where height, width and spacing of 2m was the best choice, because drivers pay the highest attention to area 5 and it did not exceed 60%, Meanwhile, the driver's fixation distribution of scheme 6 was the most stable. This study can optimize exit advance guide signs setting in the mountainous highway tunnel, then contributing to reduced traffic accidents and making mountain highway transport more sustainable.

Method of Setting Exit Advance Guide Signs in Highway Tunnels Based on the Driver’s Eye Movement With Markov Chains

While the number of highway tunnels is increasing, the current Chinese criteria and Uniform Traffic Control Equipment Manual (MUTCD) 2009 guidelines provide no clear method for setting exit advance guide signs in highway tunnels. To solve this problem, this paper proposes separate guide signs, consisting of location and distance signs. Location signs on the tops of tunnels use Chinese characters with a height of 40 cm and a width 20 cm. The distance signs are 62.6 m from the location signs with a character height and width of 1.5 m and a total sign length of 22.5 m. Four schemes were tested, in which the distance sign was on the left or right wall of the tunnel and the vehicle was in the left or right lane. At the “Perception” and “Recognition” stages, the pupil area change rate of the four schemes had a slight difference to no sign but were always less than the 20% threshold line. A Markov chain was employed to analyze the driver's eye movement characteristics to evaluate the effect of separate guide signs. The results are the following. In the left lane, when a distance sign on the left wall of the tunnel appeared, the driver's fixation points were relatively balanced, except in the left area. After the sign disappeared, the driver's fixation points were no different than before, except in the front area. However, when a distance sign appeared on the right wall, 77.84% of the driver's fixation points were concentrated in the front and right areas, which decreased the driving safety. Similar results were obtained in the right lane. Therefore, distance signs should be placed on the left wall of the highway tunnel. This study can forewarn a driver in a tunnel of the exit location and distance and help the driver to exit the highway safely.

The vergence horopter

The horopter is defined by the criterion with which it is measured; these include the apparent frontoparallel plane, the region of binocular single vision, and identical visual direction. Another criterion is one that “the positions of the points are such that none provides a stimulus for fusional movement of the eyes”. Measuring the horopter using this criterion is the aim of the current paper. Based on previous research investigating corresponding points, we predicted the vergence horopter should trace an arc similar to the empirical horizontal horopter. We further predicted based on the characteristics of vergence eye movements in the periphery, that the range of horizontal disparities that do not elicit a vergence movement would increase with eccentricity. In experiment 1 we conducted the first measurements of the vergence horopter along the horizontal plane of regard and sagittal planes. We found that the vergence horopter consists of a stable range of disparities that do not increase with eccentricity. In experiment 2, we measured Panum’s fusional range for the same eccentricities and elevations to determine the placement of the vergence horopter within the fusional ranges. In the horizontal plane, the vergence horopter sits centrally within Panum’s fusional range. In the vertical plane, the data are suggestive that the vergence horopter is less slanted than the corresponding fusional range.

Deep-learning-based reading eye-movement analysis for aiding biometric recognition

Eye-movement recognition is a new type of biometric recognition technology. Without considering the characteristics of the stimuli, the existing eye-movement recognition technology is based on eye-movement trajectory similarity measurements and uses more eye-movement features. Related studies on reading psychology have shown that when reading text, human eye-movements are different between individuals yet stable for a given individual. This paper proposes a type of technology for aiding biometric recognition based on reading eye-movement. By introducing a deep-learning framework, a computational model for reading eye-movement recognition (REMR) was constructed. The model takes the text, fixation, and text-based linguistic feature sequences as inputs and identifies a human subject by measuring the similarity distance between the predicted fixation sequence and the actual one (to be identified). The experimental results show that the fixation sequence similarity recognition algorithm obtained an equal error rate of 19.4% on the test set, and the model obtained an 86.5% Rank-1 recognition rate on the test set.

Detecting computer activities using eye-movement features

Toward the age of smart human–computer interactions, human activity recognition becomes one of the most popular areas for promoting ambient intelligence techniques. To this end, this study aimed at selecting critical eye-movement features to build artificial intelligence models for recognizing three common user activities in front of the computer using an eye tracker. One hundred fifty students participated in this study to perform three everyday computer activities, comprising reading English journal articles, typing English sentences, and watching an English trailer video. While doing these tasks, their eye-movements were recorded using a desktop eye tracker (GP3 HD Gazepoint™ Canada). The collected data were then processed as 19 eye-movement features. Before building convolutional neural network (CNN) models for recognizing the three computer activities, three feature selection methods, comprising analysis of variance (ANOVA), extra tree classification (ETC), and mutual information (MI), were used to screen critical features. For each feature selection method, the top five and top 11 selected features were then used to build six types of CNN models. For comparison, the seventh type of CNN models were developed using all the 19 features as well. The comparison of the seven types of models showed that the models that used the top 11 features screened by the ANOVA method were superior to others, with an accuracy rate of 93.15% on average. This study demonstrates the application of feature selection methods, and an alternative means to recognize user activities in front of the computer.

Electroencephalographic Findings in Pediatric Patients with Anti-N-Methyl-D-Aspartate Receptor Encephalitis: The San Diego Experience

AbstractDiagnosing anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis clinically can be challenging. There is a growing interest in identifying specific electroencephalographic features to help guide early management. A retrospective chart review was conducted of pediatric patients admitted to Rady Children's Hospital between January 1, 2010 and April 1, 2017. We included patients with the diagnosis of encephalitis who underwent continuous video electroencephalogram (VEEG) for at least 12 hours, and presented with less than 14 days of symptoms. We compared the electroencephalographic features of non-rapid eye movement (NREM) sleep between patients with antibody confirmed anti-NMDAR encephalitis and patients with encephalitis from other etiologies. We identified seven patients who met our inclusion criteria, five of whom were diagnosed with anti-NMDAR encephalitis. Four of the five patients had a significant reduction in NREM sleep, while one patient had increased NREM sleep associated with clinical catatonia and hypersomnolence. Sleep was preserved in the two cases of nonimmune mediated encephalitis. Our results suggest that a prolonged VEEG to capture sleep coupled with clinical features can aid in early diagnosis and treatment of anti-NMDAR encephalitis, often before confirmatory antibody testing is available.

Accurate detection of cerebellar smooth pursuit eye movement abnormalities via mobile phone video and machine learning

Eye movements are disrupted in many neurodegenerative diseases and are frequent and early features in conditions affecting the cerebellum. Characterizing eye movements is important for diagnosis and may be useful for tracking disease progression and response to therapies. Assessments are limited as they require an in-person evaluation by a neurology subspecialist or specialized and expensive equipment. We tested the hypothesis that important eye movement abnormalities in cerebellar disorders (i.e., ataxias) could be captured from iPhone video. Videos of the face were collected from individuals with ataxia (n = 102) and from a comparative population (Parkinson’s disease or healthy participants, n = 61). Computer vision algorithms were used to track the position of the eye which was transformed into high temporal resolution spectral features. Machine learning models trained on eye movement features were able to identify abnormalities in smooth pursuit (a key eye behavior) and accurately distinguish individuals with abnormal pursuit from controls (sensitivity = 0.84, specificity = 0.77). A novel machine learning approach generated severity estimates that correlated well with the clinician scores. We demonstrate the feasibility of capturing eye movement information using an inexpensive and widely accessible technology. This may be a useful approach for disease screening and for measuring severity in clinical trials.

What Eye Movements Reveal About Later Comprehension of Long Connected Texts.

We know that reading involves coordination between textual characteristics and visual attention, but research linking eye movements during reading and comprehension assessed after reading is surprisingly limited, especially for reading long connected texts. We tested two competing possibilities: (a) the weak association hypothesis: Links between eye movements and comprehension are weak and short-lived, versus (b) the strong association hypothesis: The two are robustly linked, even after a delay. Using a predictive modeling approach, we trained regression models to predict comprehension scores from global eye movement features, using participant-level cross-validation to ensure that the models generalize across participants. We used data from three studies in which readers (Ns=104, 130, 147) answered multiple-choice comprehension questions ~30min after reading a 6,500-word text, or after reading up to eight 1,000-word texts. The models generated accurate predictions of participants' text comprehension scores (correlations between observed and predicted comprehension: 0.384, 0.362, 0.372, ps<.001), in line with the strong association hypothesis. We found that making more, but shorter fixations, consistently predicted comprehension across all studies. Furthermore, models trained on one study's data could successfully predict comprehension on the others, suggesting generalizability across studies. Collectively, these findings suggest that there is a robust link between eye movements and subsequent comprehension of a long connected text, thereby connecting theories of low-level eye movements with those of higher order text processing during reading.

Effective schizophrenia recognition using discriminative eye movement features and model-metric based features

Eye movement abnormalities have been effective biomarkers that provide the possibility of distinguishing patients with schizophrenia from healthy controls. The existing methods for measuring eye movement abnormalities mostly focus on synchronic parameters, such as fixation duration and saccade amplitude, which can be directly obtained from eye movement data, while lack of considering more thorough features. In this paper, to better characterize eye-tracking dysfunction, we create a dataset containing 100 images with eye movement data of 40 patients and 30 healthy controls via a free-viewing task, and propose two types of features for effective schizophrenia recognition, i.e. the hand-crafted discriminative eye movement features and the model-metric based features via utilizing the computational models of fixation prediction and the metrics of evaluating their prediction performance. Using the proposed features, two commonly used classifiers including support vector machine and random forest have been trained for classification between patients and controls. Experimental results demonstrate the effectiveness of the proposed features for improving classification performance, and the potential that our method can serve as an alternative and promising approach for the computer-aided diagnosis of schizophrenia.

Watchers do not follow the eye movements of Walkers

Eye movements are a functional signature of how the visual system effectively decodes and adapts to the environment. However, scientific knowledge in eye movements mostly arises from studies conducted in laboratories, with well-controlled stimuli presented in constrained unnatural settings. Only a few studies have attempted to directly compare and assess whether eye movement data acquired in the real world generalize with those in laboratory settings, with same visual inputs. However, none of these studies controlled for both the auditory signals typical of real-world settings and the top-down task effects across conditions, leaving this question unresolved. To minimize this inherent gap across conditions, we compared the eye movements recorded from observers during ecological spatial navigation in the wild (the Walkers) with those recorded in laboratory (the Watchers) on the same visual and auditory inputs, with both groups performing the very same active cognitive task. We derived robust data-driven statistical saliency and motion maps. The Walkers and Watchers differed in terms of eye movement characteristics: fixation number and duration, saccade amplitude. The Watchers relied significantly more on saliency and motion than the Walkers. Interestingly, both groups exhibited similar fixation patterns towards social agents and objects. Altogether, our data show that eye movements patterns obtained in laboratory do not fully generalize to real world, even when task and auditory information is controlled. These observations invite to caution when generalizing the eye movements obtained in laboratory with those of ecological spatial navigation.

COVID-19 Pandemic: Euphemism and Dysphemism in Jordanian Arabic

COVID-19 is the major health crisis worldwide nowadays. Linguistic aspects of individuals and communities, including euphemism and dysphemism, were affected by this global challenge because choosing appropriate words to express what speakers intend to say and to reflect what they value or disvalue is a basic part of communication. Euphemism is an acceptable expression used instead of an offensive one to avoid unpleasant connotations, while dysphemism is a derogatory expression with negative suggestions used instead of neutral or polite one to attack something or someone. This paper investigates the use of euphemism and dysphemism in the Jordanian society for dealing with COVID-19. The research was approached from a sociolinguistic perspective and framed mainly within the Theory of Euphemism and Dysphemism by Allan and Burridge (1991; 2006) together with Warren’s model of euphemism (1992) and Lakoff and Johnson’s Conceptual Metaphor Theory (1980). A sample of 200 Jordanians was asked to respond to a questionnaire including demographic information and closed-ended and open-ended questions. The results show that the Jordanians used different euphemistic techniques in daily COVID-19 conversations, namely, metaphor, shift from Arabic into English, medical terms, and abbreviation. They show that the participants hardly adopted dysphemisms when talking about COVID-19. This paper contributes to the limited investigation of ‘pandemic discourse’, and to the understanding of euphemistic and dysphemistic tendencies of Jordanians during global crises. Researchers are recommended to explore paralinguistic features of speakers, namely, hand gestures, facial expressions, eye movements, body language, and tone and pitch of voice, while discussing COVID-19 themes.

Abnormal eye movements in patients with idiopathic rapid eye movement sleep behavior disorder

To analyze the characteristics of eye movements in patients with idiopathic rapid eye movement sleep behavior disorder (iRBD). Twenty two patients with iRBD and 20 controls were enrolled between January 2017 and May 2019 from Sir Run Run Shaw Hospital, Zhejiang University School of Medicine. Clinical data including polysomnogram (PSG) results were collected. Videonystagmography (VNG) including spontaneous nystagmus, gaze, saccade, tracking and optokinetic test were performed. The difference of VNG results between iRBD patients and controls were analyzed. The factors related to the abnormal VNG results were analyzed by using logistic regression analysis. No significant differences were found between the iRBD and control groups in the spontaneous nystagmus, gaze nystagmus, square wave jerk, involuntary eye movement, saccade and optokinetic nystagmus (all P>0.05). In smooth pursuit of 0.4-0.5 Hz and 0.6-0.7 Hz, iRBD patients had more type Ⅲ-Ⅳ curve than controls (χ2=5.177 and 5.301, both P<0.05). Logistic regression analysis indicated that less sleep time of N3 stage was related to the abnormal results in smooth pursuit of 0.4-0.5 Hz (OR=0.963, P<0.05). iRBD patients with Ⅲ-Ⅳ type curve in smooth pursuit of 0.4-0.5 Hz had less N3 sleep time than iRBD patients with Ⅰ-Ⅱ type curve (52±28 min vs. 76±23 min, t=2.197, P<0.05). Abnormal smooth pursuit was found in iRBD patients, which might be related to the pathological mechanism of iRBD.

Disease Classification Based on Eye Movement Features With Decision Tree and Random Forest.

Medical research shows that eye movement disorders are related to many kinds of neurological diseases. Eye movement characteristics can be used as biomarkers of Parkinson’s disease, Alzheimer’s disease (AD), schizophrenia, and other diseases. However, due to the unknown medical mechanism of some diseases, it is difficult to establish an intuitive correspondence between eye movement characteristics and diseases. In this paper, we propose a disease classification method based on decision tree and random forest (RF). First, a variety of experimental schemes are designed to obtain eye movement images, and information such as pupil position and area is extracted as original features. Second, with the original features as training samples, the long short-term memory (LSTM) network is used to build classifiers, and the classification results of the samples are regarded as the evolutionary features. After that, multiple decision trees are built according to the C4.5 rules based on the evolutionary features. Finally, a RF is constructed with these decision trees, and the results of disease classification are determined by voting. Experiments show that the RF method has good robustness and its classification accuracy is significantly better than the performance of previous classifiers. This study shows that the application of advanced artificial intelligence (AI) technology in the pathological analysis of eye movement has obvious advantages and good prospects.

Research on Eye Movement Characteristics of Different Level Basketball Defenders in Sports Decision-making Scenarios

Based on the study of basketball and the cognitive psychology, using the eye tracker to study the eye movements of high-level and average level basketball guard athletes, the results show that when looking at different sports situations, The ordinary basketball guard has different ways of watching, different ways of processing information and information processing efficiency. There are obvious differences in the accuracy and speed of decision-making of athletes with different levels, and the differences of sports decisions are drawn:the high-level athletes are integrated Type decision-making, while ordinary level athletes are analytical decision-making.

A Study of Eye Movement Characteristics of Children with Autism Spectrum Disorder in Reading Emotion-Themed Picture Books

본 연구는 정서 주제 그림책을 보는 동안 자폐스펙트럼장애(ASD) 유아와 일반 유아가 보이는 시각처리 차이를 객관적으로 분석하여 향후 ASD 유아의 교육적 지원에 필요한 실증적인 자료를 제공하기 위해 실시되었다. 연구대상자는 중국 절강성 항저우 시에 거주하는 ASD 유아(N=19)와 일반유아(N=19)였으며 두 집단 모두에 대해 정서를 주제로 한 동일한 그림책을 보는 동안 나타나는 주의 과정을 안구 움직임에 기반한 시각 처리로 측정하였다. 정서적 반응에 제한을 보이는 ASD 유아의 발달적 특성을 보완하고 연구에 참여한 유아들이 보이는 정서적 반응을 객관적으로 측정하기 위해 Eye-Tracker를 연구도구로 사용하였다. Eye-Tracker는 눈동자의 움직임으로 개인의 내적 반응을 객관적으로 측정할 수 있는 도구로서 많은 선행연구를 통해 유아의 정서적 반응을 효율적으로 측정할 수 있는 도구로 검증되었다. 이에 따른 연구 결과는 다음과 같다. 첫째, 일반 유아는 그림책 속 주인공의 이미지 및 정서와 관련된 영역에서 유의미하게 높은 관심을 보인 반면 ASD 유아는 그림책의 배경에 더 집중하였다. 둘째, 일반 유아는 슬픔과 노여움 등과 같은 부정적 정서를 나타내는 영역에 대해 유의미한 관심을 보였지만 ASD 유아는 기쁨과 같은 긍정적 정서를 나타내는 영역에서 유의미한 주의 집중을 나타냈다. 이러한 연구 결과를 통해 향후 ASD 유아의 정서 관련 지도 시 그림책이 중요한 매개체 역할을 할 수 있다는 것이 보고되었다. 또한, 그림책을 통한 교육적 지원 시 긍정적인 정서와 관련된 내용이 ASD 유아의 주의집중을 높일 수 있으며 부정적 정서를 포함하는 경우 충분한 시간을 제공해서 유아가 그림책을 탐색할 수 있도록 지도해야 한다는 것이 제시되었다.

Microsaccades: Empirical Research and Methodological Advances - Introduction to Part 1 of the Thematic Special Issue.

Microsaccades: Empirical Research and Methodological Advances - Introduction to Part 1 of the Thematic Special Issue.

Eye movement characteristics for the types of mathematics patterning in young children

Eye movement characteristics for the types of mathematics patterning in young children