One of the most effective ways to improve quality of life in dementia is by exposing people to meaningful activities. The study of engagement is crucial to identify which activities are significant for persons with dementia and customize them. Previous work has mainly focused on developing assessment tools and the only available model of engagement for people with dementia focused on factors influencing engagement or influenced by engagement. This article focuses on the internal functioning of engagement and presents the development and testing of a model specifying the components of engagement, their measures, and the relationships they entertain. We collected behavioral and physiological data while participants with dementia (N = 14) were involved in six sessions of play, three of game-based cognitive stimulation and three of robot-based free play. We tested the concurrent validity of the measures employed to gauge engagement and ran factorial analysis and Structural Equation Modeling to determine whether the components of engagement and their relationships were those hypothesized. The model we constructed, which we call the ENGAGE-DEM, achieved excellent goodness of fit and can be considered a scaffold to the development of affective computing frameworks for measuring engagement online and offline, especially in HCI and HRI.

This study examines patterns of coordinated gaze between a child and a robot (NAO) during a card matching game, `Memory'. Dyadic gaze behavior like mutual gaze, gaze following and joint attention are indications both of child's engagement with the robot and of the quality of child-robot interaction. Eighteen children interacted with a robot tutor in two settings. In the first setting, the robot tutor gave clues to assist children in finding the matching cards, and in the other setting, the robot tutor only looked at the participants during the play. We investigated the coordination between child and robots' gaze behaviors. We found that more occurrences of mutual gaze and gaze following made the children aware of the gaze hints given by the robot and improved the efficacy of the robot tutor as a helping agent. This study, therefore, provides guidelines for gaze behaviors design to enrich child-robot interaction in a tutoring context.

This paper presents a study that analyzes the effects of robots' gaze hints on children's performance in a card-matching game. We conducted a within-subjects study, in which children played a card matching game "Memory" in the presence of a robot tutor in two sessions. In one session, the robot gave hints to help the child find matching cards by looking at the correct match and, in the other session, the robot only looked at the child and did not give them any help. Children performance was measured using the number of tries and overall time used to complete the game. Our findings show that the use of gaze hints (help condition) made the matching task significantly easier and that children used significantly fewer tries than without help.

The study of engagement is central to improve the quality of care and provide people with dementia with meaningful activities. Current assessment techniques of engagement for people with dementia rely exclusively on behavior observation. However, novel unobtrusive sensing technologies, capable of tracking psychological states during activities, can provide us with a deeper layer of knowledge about engagement. We compared the engagement of persons with dementia involved in two playful activities, a game-based cognitive stimulation and a robot-based free play, using observational rating scales and electrodermal activity (EDA). Results highlight significant differences in observational rating scales and EDA between the two activities and several significant correlations between the items of observational rating scales of engagement and affect, and EDA features.

Gaze is an important nonverbal cue in human - human communication, for example, in communicating direction of attention. Therefore, presumably being able to understand and provide gaze cues is an important aspect in robot's interactive behavior. While there is considerable progress, as regards the design of social gaze cues for robots, there is little that has been done to examine the ability of humans to read and accept help signals from a robot's gaze. In this study, we examine how people perceive gaze cues and head angles directed towards different target positions on a table when human and NAO robot are sitting against each other as in board game scenarios. From the results, we show that when the head pitch angle is higher (24±2) and the depth is less, approximately 20 cm from the robot, participants detected the positions with good accuracy. Unexpectedly, the locations on the left of the robot were detected with lower accuracy. In conclusion, we discuss the implications of this research for design of interaction settings between human and a robot that is intended for social and educational support.

In the past decade, research on human–computer interaction has embraced psychophysiological user interfaces that enhance awareness of computers about conscious cognitive and affective states of users and increase their adaptive capabilities. Still, human experience is not limited to the levels of cognition and affect but extends further into the realm of universal instincts and innate behaviours that form the collective unconscious. Patterns of instinctual traits shape archetypes that represent images of the unconscious. This study investigated whether seven various archetypal experiences of users lead to recognisable patterns of physiological responses. More specifically, the potential of predicting the archetypal experiences by a computer from physiological data collected with wearable sensors was evaluated. The subjects were stimulated to feel the archetypal experiences and conscious emotions by means of film clips. The physiological data included measurements of cardiovascular and electrodermal activities. Statistical analysis indicated a significant relationship between the archetypes portrayed in the videos and the physiological responses. Data mining methods enabled us to create between-subject prediction models that were capable of classifying four archetypes with an accuracy of up to 57.1%. Further analysis suggested that classification performance could be improved up to 70.3% in the case of seven archetypes by using within-subject models.

In order to observe spatial relationships in social human-robot interactions, a field trial was carried out within the CosmoCaixa Science Museum in Barcelona. The follow me episodes studied showed that the space configurations formed by guide and visitors walking together did not always fit the robot social affordances and navigation requirements to perform the guidance successfully, thus additional communication prompts are considered to regulate effectively the walking together and follow me behaviours.

This paper presents an analysis of two comparable studies with LEGO Robotics-based activities in a social skills training program for children with autism spectrum disorders (ASD). One study has been carried out with a group of 16 children in the Unit of Pediatrics Psychology and Psychiatry in HSJD in Barcelona, Spain and the other with a group of 17 children at the Center for Education and Engineering Outreach (Tufts U.) in Boston, USA. The aim of this comparison is discuss lessons learnt and develop empirical based guidelines for intervention design.

Emotional factors related to aging at home assistive technology are known to affect technology acceptance, effective use, and quality of life improvement. This paper is a survey on the affective dimension of robot-based systems conceived for helping elderly at home. The specificity of elders' capabilities (e.g. sensory and cognitive), coping styles, aspirations, lifestyles, social rules and preferences are faced with available knowledge from the fields of social psychology, sociology and gerontology. In the case of social robots, convenient verbal and non-verbal communication and motion behavior (e.g. social distance, space formations) are to be designed according to generational and cultural rules. Moreover, robot behavior should be congruent with its role (i.e. helper, companion) and affordances.

This paper presents a study on (1) how children experience a pet robot, (2) how they play with it and (3) how children's perceptions on and interaction with pet robots are interrelated. The study features different types of subjective and objective techniques to assess the degree of perceived social entity from self-reports (i.e. questionnaires) and observed behavior. Three short questionnaires and an ad hoc code scheme of 15 low-level micro-behaviors were developed. 28 scholars aged 8 to 12 were observed at school during a play period with a Pleo robot and asked to answer the questionnaires. We found that the different questionnaire based methods were in line each other. Therefore, anyone of them can be used to measure the experience of a social entity. Play analyses showed that the two most prevalent behaviors were clearly social: petting the robot and showing it objects to engage in interaction. Moreover, children spent on average less than one per cent of the session time treating the robot as an artifact. However, significant covariation between the experience of a social entity and observed behavior could not be established.

This work explores the dynamics of the emergence of the social bonds with robots. A field study with 49 sixth grade scholars (aged 11-12 years) and 4 different robots was carried out at an elementary school. A subsequent laboratory experiment with 4 of the participants was completed. For the first experience, at school children's preferences, expectancies on functionality and communication, and interaction behavior were studied. Using the data collected in the laboratory, recognition, the selection of partner, and dyadic interaction were explored. Both at school and in the lab, data from videotaped direct observation, questionnaires and interviews were gathered. The results showed that different appearance and performance of robots elicit in children distinctive perceptions and interactive behavior, and affect social processes, such as role attribution and attachment. This work presents a preliminary field study to explore the introduction of robot-based programs to improve the quality of life of hospitalized children.

Abstract Summary: AStream, an R-statistical software package for the curation and identification of feature peaks extracted from liquid chromatography mass spectrometry (LC/MS) metabolomics data, is described. AStream detects isotopic, fragment and adduct patterns by identifying feature pairs that fulfill expected relational patterns. Data reduction by AStream allows compounds to be identified reliably and subsequently linked to metabolite databases. AStream provides researchers with a fast, reliable tool for summarizing metabolomic data, notably reducing curation time and increasing consistency of results. Availability: The AStream R package and a study example can be freely accessed at http://www.urr.cat/AStream/AStream.html. Contact: [email protected]; [email protected] Supplementary information: Supplementary data are available at Bioinformatics online.