Search Results (29)

Mobile eye tracking is an important tool in psychology and human-centered interaction design for understanding how people process visual scenes and user interfaces. However, analyzing recordings from head-mounted eye trackers, which typically include an egocentric video of the scene and a gaze signal, is a time-consuming and largely manual process. To address this challenge, we develop eyeNotate, a web-based annotation tool that enables semi-automatic data annotation and learns to improve from corrective user feedback. Users can manually map fixation events to areas of interest (AOIs) in a video-editing-style interface (baseline version). Further, our tool can generate fixation-to-AOI mapping suggestions based on a few-shot image classification model (IML-support version). We conduct an expert study with trained annotators (n = 3) to compare the baseline and IML-support versions. We measure the perceived usability, annotations’ validity and reliability, and efficiency during a data annotation task. We asked our participants to re-annotate data from a single individual using an existing dataset (n = 48). Further, we conducted a semi-structured interview to understand how participants used the provided IML features and assessed our design decisions. In a post hoc experiment, we investigate the performance of three image classification models in annotating data of the remaining 47 individuals. Full article

High Andean ecosystems face increasing pressures that threaten the sustainability of rural livelihoods, prompting communities to demand culturally appropriate governance responses. This study examines the structure of environmental concern in two rural communities, Riobamba and Guaranda, in the central Ecuadorian Andes. Applying a tripartite model of egocentric, altruistic, and biocentric concern, we assess its validity through Confirmatory Factor Analysis (CFA) and evaluate the influence of age, gender, ethnicity, and economic activity using Structural Equation Modeling (SEM). The results reveal distinct patterns: biocentric concern predominates in the more urbanized Riobamba, while Guaranda shows a stronger egocentric orientation, accompanied by moderate altruistic concern. Agricultural activity and residence in less urbanized environments are associated with lower levels of environmental concern, whereas age, gender, and ethnicity show no significant effects. The results suggest that although there are differences in the forms of environmental concern, these dimensions are not isolated. Instead, they are part of the same hierarchical phenomenon. This analysis supports the idea of a general concept of a relationship with nature. These findings underscore the importance of implementing environmental policies that respect the holistic worldview of Andean communities. They also highlight the need to develop culturally sensitive measurement tools to avoid potential biases and ensure alignment with local realities. Full article

Influential studies in the history of cartography have argued that map-like representations of space were (virtually) unknown in the Classical Mediterranean world and that the cause of this was an absence of underlying cognitive maps. That is, persons in that time/place purportedly had only route/egocentric-type mental representations, not survey/allocentric ones. The present study challenges that cognitive claim by examining the verbal descriptions of plots of land produced by ancient Roman land-measurers. Despite the prescription of a route-based form, actual representations persistently show a variety of features which suggest the existence of underlying survey-type mental models and the integration of those with the route-type ones. This fits better with current views on interaction between types of spatial representation and of cultural difference in this area. The evidence also suggests a linkage between the two kinds of representations. Full article

Social support has been associated with viral suppression among persons living with HIV (PWH). We examined cross-sectional data from young Black men who have sex with men to see if sociodemographic factors, medical history, and egocentric Facebook social support measures are related to viral suppression. Differences between participants were examined using Chi-square, Fisher’s exact, or Wilcoxon Rank Sum Tests, with significance set at p = 0.10. Degree centrality (p = 0.074) and Eigenvector centrality (p = 0.087) were significant, indicating that PWH with unsuppressed viral loads had more social connections. These results contrast prior studies in the literature. Further research on online social support for PWH is needed. Full article

Bullying is a social problem that usually increases during adolescence and can have serious consequences on the wellbeing of students. One of the members of the educational community that is most present in these situations is the teachers. This qualitative research aims to know the teachers’ perceptions about bullying among adolescents within the school environment. It was possible to deepen the experiences of 20 teachers by conducting semistructured interviews with open-ended questions. The results obtained indicate that education professionals have been bystanders to episodes of bullying among their students and that they opt for mediation between both parties (bully and victim) as an intervention measure. Teachers believe that bullied students tend to be young people with low self-esteem, introverted and sad. On the contrary, bullies are shown to be leaders with social support, egocentric, and with low empathy. The need to know the different perceptions and strategies used by teachers in situations of bullying among their students is discussed, with the intention of promoting resources and programs that can help them in this type of situation. Full article

Background: Spatial navigation deficits are reported as early symptoms of Alzheimer’s disease (AD) alongside episodic memory ones. The aim of the present study was to ascertain whether neuropsychological deficits of visuospatial long-term memory can predict behavioral alterations during the navigation of older adults in novel urban environments along the normal aging–dementia continuum of the Alzheimer’s type. Methods: A total of 24 community-dwelling patients with Mild Cognitive Impairment (MCI) due to AD, 27 individuals with subjective cognitive decline (SCD), and 21 healthy controls were assessed in terms of their sequential egocentric and allocentric navigation abilities by using a modified version of the Detour Navigation Test, and neuropsychologically tested by the Corsi learning suvra-span (CLSS) test. Generalized linear models were adopted to verify whether the scores obtained by the three groups in the CLSS test predicted wrong turns and moments of hesitation during the navigation task, with the results presented as topographical disorientation scores. Results: Higher scores in the CLSS test predicted fewer wrong turns (b = −0.05; z = −2.91; p = 0.004; net of between-groups differences) and moments of hesitation for patients with MCI due to AD (b = −0.14; z = −2.43; p = 0.015), and individuals with SCD (b = −0.17; z = −3.85; p < 0.001). Conclusions: Since the CLSS test has been reported to be a reliable measure of ecological navigational abilities in the progression towards AD dementia, we recommend its use in clinical practice and highlight implications for future research. Full article

Robotaxi, coined from “robot” and “taxi”, refers to a taxi service with vehicles controlled by self-driving algorithms instead of human drivers. Despite the availability of such a service, it is yet unknown whether customers will adopt robotaxi, given its immaturity. Meanwhile, the potential customers of the robotaxi service are facing an inescapable ethics issue, the “trolley dilemma”, which might have a strong impact on their adoption of the service. Based on the necessity of understanding robotaxi adoption, especially from an ethical point of view, this study aims to uncover and quantify the antecedents of robotaxi adoption, taking the trolley dilemma into consideration. We applied a modified Unified Theory of Acceptance and Use of Technology (UTAUT) framework to explore the antecedents of robotaxi adoption, with a special focus on customers’ understanding of the trolley dilemma. We conducted online surveys (N = 299) to obtain the customers’ opinions regarding robotaxis. Aside from measuring standard variables in UTAUT, we developed four proprietary items to measure trolley dilemma relevance. We also randomly assigned the participants to two groups, either group A or group B. Participants in group A are told that all robotaxis are programmed with a utilitarian algorithm, such that when facing a trolley dilemma, the robotaxi will conditionally compromise the passenger(s) to save a significantly larger group of pedestrians. In the meantime, participants in group B are informed that all robotaxis are programmed with an egocentric algorithm, such that when facing a trolley dilemma, the robotaxi will always prioritize the safety of the passenger(s). Our findings suggest that both performance expectancy and effort expectancy have a positive influence on robotaxi adoption intention. As for the trolley dilemma, customers regard it as of high relevance to robotaxis. Moreover, if the robotaxi is programmed with an egocentric algorithm, the customers are significantly more willing to adopt the service. Our paper contributes to both adoption studies and ethics studies. We add to UTAUT two new constructs, namely trolley dilemma relevance and trolley dilemma algorithm, which can be generalized to adapt to other new technologies involving ethics issues. We also directly ask customers to assess the relevance and algorithm of the trolley dilemma, which is a meaningful supplement to existing ethics studies that mostly debate from researchers’ perspectives. Meanwhile, our paper is managerially meaningful as it provides solid suggestions for robotaxi companies’ marketing campaigns. Full article

The analysis of complex and time-evolving interactions, such as those within social dynamics, represents a current challenge in the science of complex systems. Temporal networks stand as a suitable tool for schematizing such systems, encoding all the interactions appearing between pairs of individuals in discrete time. Over the years, network science has developed many measures to analyze and compare temporal networks. Some of them imply a decomposition of the network into small pieces of interactions; i.e., only involving a few nodes for a short time range. Along this line, a possible way to decompose a network is to assume an egocentric perspective; i.e., to consider for each node the time evolution of its neighborhood. This was proposed by Longa et al. by defining the “egocentric temporal neighborhood”, which has proven to be a useful tool for characterizing temporal networks relative to social interactions. However, this definition neglects group interactions (quite common in social domains), as they are always decomposed into pairwise connections. A more general framework that also allows considering larger interactions is represented by higher-order networks. Here, we generalize the description of social interactions to hypergraphs. Consequently, we generalize their decomposition into “hyper egocentric temporal neighborhoods”. This enables the analysis of social interactions, facilitating comparisons between different datasets or nodes within a dataset, while considering the intrinsic complexity presented by higher-order interactions. Even if we limit the order of interactions to the second order (triplets of nodes), our results reveal the importance of a higher-order representation.In fact, our analyses show that second-order structures are responsible for the majority of the variability at all scales: between datasets, amongst nodes, and over time. Full article

Modeling the perception and evaluation of landscapes from the human perspective is a desirable goal for several scientific domains and applications. Human vision is the dominant sense, and human eyes are the sensors for apperceiving the environmental stimuli of our surroundings. Therefore, exploring the experimental recording and measurement of the visual landscape can reveal crucial aspects about human visual perception responses while viewing the natural or man-made landscapes. Landscape evaluation (or assessment) is another dimension that refers mainly to preferences of the visual landscape, involving human cognition as well, in ways that are often unpredictable. Yet, landscape can be approached by both egocentric (i.e., human view) and exocentric (i.e., bird’s eye view) perspectives. The overarching approach of this review article lies in systematically presenting the different ways for modeling and quantifying the two ‘modalities’ of human perception and evaluation, under the two geometric perspectives, suggesting integrative approaches on these two ‘diverging’ dualities. To this end, several pertinent traditions/approaches, sensor-based experimental methods and techniques (e.g., eye tracking, fMRI, and EEG), and metrics are adduced and described. Essentially, this review article acts as a ‘guide-map’ for the delineation of the different activities related to landscape experience and/or management and to the valid or potentially suitable types of stimuli, sensors techniques, and metrics for each activity. Throughout our work, two main research directions are identified: (1) one that attempts to transfer the visual landscape experience/management from the one perspective to the other (and vice versa); (2) another one that aims to anticipate the visual perception of different landscapes and establish connections between perceptual processes and landscape preferences. As it appears, the research in the field is rapidly growing. In our opinion, it can be greatly advanced and enriched using integrative, interdisciplinary approaches in order to better understand the concepts and the mechanisms by which the visual landscape, as a complex set of stimuli, influences visual perception, potentially leading to more elaborate outcomes such as the anticipation of landscape preferences. As an effect, such approaches can support a rigorous, evidence-based, and socially just framework towards landscape management, protection, and decision making, based on a wide spectrum of well-suited and advanced sensor-based technologies. Full article

There have been sustained efforts toward using naturalistic methods in developmental science to measure infant behaviors in the real world from an egocentric perspective because statistical regularities in the environment can shape and be shaped by the developing infant. However, there is no user-friendly and unobtrusive technology to densely and reliably sample life in the wild. To address this gap, we present the design, implementation and validation of the EgoActive platform, which addresses limitations of existing wearable technologies for developmental research. EgoActive records the active infants’ egocentric perspective of the world via a miniature wireless head-mounted camera concurrently with their physiological responses to this input via a lightweight, wireless ECG/acceleration sensor. We also provide software tools to facilitate data analyses. Our validation studies showed that the cameras and body sensors performed well. Families also reported that the platform was comfortable, easy to use and operate, and did not interfere with daily activities. The synchronized multimodal data from the EgoActive platform can help tease apart complex processes that are important for child development to further our understanding of areas ranging from executive function to emotion processing and social learning. Full article

An animal’s ability to navigate its home range in search of essential resources is a key aspect of its ecology. To reach these resources, animals employ varying navigational processes depending on their exocentric or egocentric view of their environment. The goal of this study was to determine if the Javan slow loris (Nycticebus javanicus), a nocturnal arboreal primate found in southeast Asia, uses some form of cognitive map and spatial memory while navigating their environment. Using behavioural and GPS data of six males and seven females collected at the Little Fireface Project field station based in West Java, Indonesia, we measured their frequency of revisiting important feeding trees, route overlap, and points where individuals significantly changed directions. We found that all individuals predominantly used four tree species while feeding and foraging. The lorises also displayed a high level of route overlap, leading us to conclude that they likely utilize a route-based cognitive map where certain landmarks are integral to their nightly movement. Few studies have specifically focused on strepsirrhine spatial cognition in the wild; here, we show the navigational mechanism used by the Javan slow loris to reach distant/out-of-sight resources. The evident reliance on spatial cognition in a strepsirrhine species suggest that it could be an important selective pressure for primates at the earliest stages of primate cognitive evolution. In addition to the importance of spatial memory in theoretical discourse, understanding slow loris movement has practical applications to conservation, particularly regarding the numerous translocations undertaken by individuals rescued from the illegal wildlife trade. We discuss the importance of considering soft release training and monitoring in such releases. Full article

Despite the automatization of many industrial and logistics processes, human workers are still often involved in the manual handling of loads. These activities lead to many work-related disorders that reduce the quality of life and the productivity of aged workers. A biomechanical analysis of such activities is the basis for a detailed estimation of the biomechanical overload, thus enabling focused prevention actions. Thanks to wearable sensor networks, it is now possible to analyze human biomechanics by an inverse dynamics approach in ecological conditions. The purposes of this study are the conceptualization, formulation, and implementation of a deep learning-assisted fully wearable sensor system for an online evaluation of the biomechanical effort that an operator exerts during a manual material handling task. In this paper, we show a novel, computationally efficient algorithm, implemented in ROS, to analyze the biomechanics of the human musculoskeletal systems by an inverse dynamics approach. We also propose a method for estimating the load and its distribution, relying on an egocentric camera and deep learning-based object recognition. This method is suitable for objects of known weight, as is often the case in logistics. Kinematic data, along with foot contact information, are provided by a fully wearable sensor network composed of inertial measurement units. The results show good accuracy and robustness of the system for object detection and grasp recognition, thus providing reliable load estimation for a high-impact field such as logistics. The outcome of the biomechanical analysis is consistent with the literature. However, improvements in gait segmentation are necessary to reduce discontinuities in the estimated lower limb articular wrenches. Full article

Safety plays a key role in human–robot interactions in collaborative robot (cobot) applications. This paper provides a general procedure to guarantee safe workstations allowing human operations, robot contributions, the dynamical environment, and time-variant objects in a set of collaborative robotic tasks. The proposed methodology focuses on the contribution and the mapping of reference frames. Multiple reference frame representation agents are defined at the same time by considering egocentric, allocentric, and route-centric perspectives. The agents are processed to provide a minimal and effective assessment of the ongoing human–robot interactions. The proposed formulation is based on the generalization and proper synthesis of multiple cooperating reference frame agents at the same time. Accordingly, it is possible to achieve a real-time assessment of the safety-related implications through the implementation and fast calculation of proper safety-related quantitative indices. This allows us to define and promptly regulate the controlling parameters of the involved cobot without velocity limitations that are recognized as the main disadvantage. A set of experiments has been realized and investigated to demonstrate the feasibility and effectiveness of the research by using a seven-DOF anthropomorphic arm in combination with a psychometric test. The acquired results agree with the current literature in terms of the kinematic, position, and velocity aspects; use measurement methods based on tests provided to the operator; and introduce novel features of work cell arranging, including the use of virtual instrumentation. Finally, the associated analytical–topological treatments have enabled the development of a safe and comfortable measure to the human–robot relation with satisfactory experimental results compared to previous research. Nevertheless, the robot posture, human perception, and learning technologies would have to apply research from multidisciplinary fields such as psychology, gesture, communication, and social sciences in order to be prepared for positioning in real-world applications that offer new challenges for cobot applications. Full article

The importance of an external interaction interface (eHMI) has grown in recent years. Most eHMI concepts focus on communicating autonomous vehicle (AV)’s yielding intention to pedestrians at a crossing. However, according to previous studies, pedestrians at a crossing rely mainly on the vehicle’s movement information (implicit communication) rather than information from eHMIs (explicit communication). This paper has the purpose of proposing a specific use case in which the eHMI of future AVs could play an indispensable role in the safety of other road users (ORUs). Often VRUs cannot see the traffic flow due to a series of parked or stopped vehicles, which is a frequent cause of fatal traffic collision accidents. Drivers may also not be able to see approaching pedestrians or other cars from the side for the same reason. In this paper, the impact of an eHMI is tested from the perspective of drivers with limited visibility when a jaywalker steps into the road. A combination of colors, shapes, and information levels is presented on an eHMI. We show that our proposed eHMI design, in the deadlock scenario of a jaywalker and a driver who both lack visibility, significantly reduced the reaction time compared to when there was no eHMI. In the experiment, the willingness to stop, varying from 0 to 5, was measured from the driver’s perspective. The results showed that most users felt uncertainty and did not move quickly when seeing the light band color alone. Textual information on the eHMI was significantly more effective in providing an urgent warning of this specific scenario than vertical and horizontal light bands with color without text. In addition, red color, blinking rapidly above 3 Hz, and egocentric messages were also necessary to reduce the PRT(perception response time). By using text-added eHMI (Vertical + Text eHMI), the mean time to achieve a score above 4 for willingness to stop was 2.113 s faster than when there was no eHMI. It was 2.571 s faster than the time until the slider of the participants reached the maximum level for willingness to stop. This is a meaningful amount of difference when considering a PRT of 2.5 s, which is the Korean road design standard. As eHMIs tend to be applied for smarter mobility, it is expected that they will be more effective in preventing accidents if the eHMI is standardized in autonomous driving level 2 to 3 vehicles driven by humans before fully autonomous driving becomes a reality. Full article

The second language acquisition (SLA) field has recently seen heightened interest in the study and application of positive psychology (PP). Emotion regulation is one of the concepts that has been stressed in PP. Several studies in PP have delved into how controlling one’s emotions improves second language learning/teaching. One of the concepts that has slipped the minds of researchers in the field is altruistic teaching. Unlike egocentric acts, altruistic teaching acts are performed to improve others’ well-being. Despite their importance in causing positive emotional effects, no study has investigated the impact of altruistic teaching acts on learners’ emotion regulation. To bridge this gap, the present study sought to investigate the effect of learners’ altruistic teaching on their emotion regulation. The study followed a sequential explanatory comparison group pre-test–post-test design. One hundred forty-one English as a Foreign Language (EFL) learners were recruited for this intervention study and were divided into experimental and control groups. Learners in the experimental group performed altruistic teaching by teaching their peers how to write essays in English, whereas learners in the control group did group work tasks on English essay writing. The results of independent-sample t-tests and repeated-measures ANOVA showed that altruistic teaching significantly impacts EFL learners’ emotion regulation. The results of qualitative data pointed to five themes, including enjoyment, self-esteem, bonding, devotion, and progress. Overall, the results suggested that altruistic teaching impacts learners’ emotion regulation by enhancing their enjoyment, self-esteem, bonding, devotion, and progress. The paper has theoretical and pedagogical implications for SLA research and practice. Full article