Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review <s> Data Collection <s> Holmqvist, K., Nystrom, N., Andersson, R., Dewhurst, R., Jarodzka, H., & Van de Weijer, J. (Eds.) (2011). Eye tracking: a comprehensive guide to methods and measures, Oxford, UK: Oxford University Press. <s> BIB001 </s> Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review <s> Data Collection <s> We investigated rapid object categorization and, more specifically, the ability to detect a target object within a natural scene in people with mild Alzheimer's disease (AD) using a saccadic choice task. It has been suggested that the anatomical pathway likely used to initiate rapid oculomotor responses in the saccadic choice task could involve the Frontal Eye Field, a structure that is part of the dorsal attentional network, in which connectivity is disrupted in AD. Seventeen patients with mild AD and 23 healthy age-matched controls took part in the study. A group of 24 young healthy observers was included as it has been reported that normal aging affects eye movements. Participants were presented with pairs of colored photographs of natural scenes, one containing an animal (the target) and one containing various objects (distracter), displayed for 1 s left and right of fixation. They were asked to saccade to the scene containing an animal. Neither pathology nor age affected temporal (saccade latencies and durations) and spatial (saccade amplitude) parameters of eye movements. Patients with AD were significantly less accurate than age-matched controls, and older participants were less accurate than young observers. The results are interpreted in terms of noisier sensory information and increased uncertainty in relation to deficits in the magnocellular pathway. The results suggest that, even at a mild stage of the pathology, people exhibit difficulties in selecting relevant objects. <s> BIB002 </s> Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review <s> Data Collection <s> Visually-guided behavior recruits a network of brain regions so extensive that it is often affected by neuropsychiatric disorders, producing measurable atypical oculomotor signatures. Wang et al. (2015) combine eye tracking with computational attention models to decipher the neurobehavioral signature of autism. <s> BIB003 </s> Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review <s> Data Collection <s> Reading requires the integration of several central cognitive subsystems, ranging from attention and oculomotor control to word identification and language comprehension. Reading saccades and fixations contain information that can be correlated with word properties. When reading a sentence, the brain must decide where to direct the next saccade according to what has been read up to the actual fixation. In this process, the retrieval memory brings information about the current word features and attributes into working memory. According to this information, the prefrontal cortex predicts and triggers the next saccade. The frequency and cloze predictability of the fixated word, the preceding words and the upcoming ones affect when and where the eyes will move next. In this paper we present a diagnostic technique for early stage cognitive impairment detection by analyzing eye movements during reading proverbs. We performed a case-control study involving 20 patients with probable Alzheimer's disease and 40 age... <s> BIB004 </s> Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review <s> Data Collection <s> Visual analytics of eye tracking data is a common tool for evaluation studies across diverse fields. In this position paper we propose a novel user-driven interactive data exploration tool for understanding the characteristics of eye gaze movements and the changes in these behaviours over time. Eye tracking experiments generate multidimensional scan path data with sequential information. Many mathematical methods in the past have analysed one or a few of the attributes of the scan path data and derived attributes such as Area of Interest (AoI), statistical measures, geometry, domain specific features etc. In our work we are interested in visual analytics of one of the derived attributes of sequential data-the: AoI and the sequences of visits to these AoIs over time. In the case of static stimuli, such as images, or dynamic stimuli, like videos, having predefined or fixed AoIs is not an efficient way of analysing scan path patterns. The AoI of a user over a stimulus may evolve over time and hence determining the AoIs dynamically through temporal clustering could be a better method for analysing the eye gaze patterns. In this work we primarily focus on the challenges in analysis and visualization of the temporal evolution of AoIs. This paper discusses the existing methods, their shortcomings and scope for improvement by adopting visual analytics methods for event-based temporal data to the analysis of eye tracking data. <s> BIB005 </s> Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review <s> Data Collection <s> Vision is an active process in that detailed representations of our visual world are only built from actively scanning our eyes with a series of saccades and fixations. The process of actively scanning a visual scene while looking for something in a cluttered environment is known as visual search. The study of visual search processes not only offers a unique opportunity to gain fundamental insights into visual information processing in the human brain, but also opens new avenues to assess cognitive function. In this work, we show that it is possible to unveil the strategies pursued by subjects to solve visual tasks by investigating dynamical aspects inherent to eye-tracking data in a generalized N-dimensional feature domain. <s> BIB006 </s> Computational Techniques for Eye Movements Analysis towards Supporting Early Diagnosis of Alzheimer's Disease: A Review <s> Data Collection <s> Patients with Alzheimer's disease (AD) develop progressive language, visuoperceptual, attentional, and oculomotor changes that can have an impact on their reading comprehension. However, few studies have examined reading behavior in AD, and none have examined the contribution of predictive cueing in reading performance. For this purpose we analyzed the eye movement behavior of 35 healthy readers (Controls) and 35 patients with probable AD during reading of regular and high- predictable sentences. The cloze predictability of words N - 1, and N + 1 exerted an influence on the reader's gaze duration. The predictabilities of preceding words in high-predictable sentences served as task-appropriate cues that were used by Control readers. In contrast, these effects were not present in AD patients. In Controls, changes in predictability significantly affected fixation duration along the sentence; noteworthy, these changes did not affect fixation durations in AD patients. Hence, only in healthy readers did predictability of upcoming words influence fixation durations via memory retrieval. Our results suggest that Controls used stored information of familiar texts for enhancing their reading performance and imply that contextual-word predictability, whose processing is proposed to require memory retrieval, only affected reading behavior in healthy subjects. In AD patients, this loss reveals impairments in brain areas such as those corresponding to working memory and memory retrieval. These findings might be relevant for expanding the options for the early detection and monitoring in the early stages of AD. Furthermore, evaluation of eye movements during reading could provide a new tool for measuring drug impact on patients' behavior. <s> BIB007
To collect data, an important step is choosing a proper eye tracker device according to a planned research study. Eye trackers are devices that measure the point of gaze or eye movements from an individual BIB005 . The availability of eye movements recordings allows researchers to gather and analyze ground truth data about visual exploration BIB006 . This feature makes eye trackers a useful tool to study changes in cognition through eye movements analysis  BIB003 . The cognitive process are not directly measured with eye trackers. We can manipulate independent variables according to experimental design setups and measure the behavioral response from participants with eye movements measures BIB001 . Eye tracking provides a noninvasive tool without contraindications suitable for potential screening and tracking of AD  . Eye trackers provide data sensitivity that makes them suitable for analyzing oculomotor abnormalities in AD. However, there are different technological approaches for the construction of eye trackers BIB001 . For this reason, it is important to choose properly the adequate eye tracker features that fit the study. Eye trackers can be static or provide mobility. For example, there are screen-based eye trackers, as the one used in BIB004 . These types of eye trackers are desktop mounted and collect fixation points only from the gaze towards the content displayed on a screen. Another type of eye trackers is head mounted, as the "ExpressEye" used in  . In this case the device allows capturing gaze fixations not limited to a specific screen; however, the user can not freely move because the apparatus is cumbersome. Nowadays, there are available commercial mobile eye trackers, such as Tobbi© (https://www.tobiipro.com) or SMI© (https://www.smivision.com) that provide continuous, remote, and pervasive capture capabilities. These capabilities are desirable to analyze eye movements from PwAD in naturalistic scenarios. Despite capabilities provided by eye trackers, there are concerns about the use of eye trackers when participants are unrestrained  . The concerns are about the reliability of gaze recording when capturing data when participants take a nonoptimal pose. This later might represent a challenge in naturalistic experimental setups. To gather data from participants in AD studies, researches divide participants into groups. Usually, the groups reported in the literature are young controls, elder controls, and PwAD. However, there are studies that also include a group people with Mild Cognitive Decline (MCI) to differentiate between persons in a more advanced stage of AD. The cognitive status from participants is usually evaluated through neuropsychological tests, such as the Mini Mental State Examination (MMSE) BIB002 . However, some studies have used other techniques such as thyroid function test and magnetic resonance images BIB007 among others. The participants perform instructed oculomotor tasks while observing visual stimuli, such as images or video. The fixation points from the participants are collected using the chosen eye tracking device. Then, statistical tests and other modeling techniques are applied for data analysis. Finally, results are presented correlating outcome measures with a cognitive status and by showing differences among control groups and PwAD if present. In the next section different approaches that have encountered relation between eye movements and AD under different experimental setups are described.