Objective: The PAL project develops a conversational agent with a physical (robot) and virtual (avatar) embodiment to support diabetes self-management of children ubiquitously. This paper assesses 1) the effect of perceived similarity between robot and avatar on children's' friendship towards the avatar, and 2) the effect of this friendship on usability of a self-management application containing the avatar (a) and children's motivation to play with it (b). Methods: During a four-day diabetes camp in the Netherlands, 21 children participated in interactions with both agent embodiments. Questionnaires measured perceived similarity, friendship, motivation to play with the app and its usability. Results: Children felt stronger friendship towards the physical robot than towards the avatar. The more children perceived the robot and its avatar as the same agency, the stronger their friendship with the avatar was. The stronger their friendship with the avatar, the more they were motivated to play with the app and the higher the app scored on usability. Conclusion: The combination of physical and virtual embodiments seems to provide a unique opportunity for building ubiquitous long-term child-agent friendships. Practice implications: an avatar complementing a physical robot in health care could increase children's motivation and adherence to use self-management support systems. (c) 2018 Elsevier B.V. All rights reserved.

We are developing a social robot that helps children with diabetes Type 1 to acquire self-management skills and routines. There is a diversity of Behavior Change Techniques (BCTs) and guidelines that seem to be useful for the development of such support, but it is not yet clear how to work out the techniques into concrete robot support functions and behaviors. The situated Cognitive Engineering (sCE) methodology provides guidance for the design and evaluation of such functions and behaviors, but doesn’t provide a univocal specification method of the theoretical and empirical justification. This paper presents an extension of sCE: a formal template that describes the relations between support objectives, behavior change theory, design specifications and evaluation outcomes, called situated Design Rationale (sDR) and the method to get this. As test case, the European ALIZ-e project is used to instantiate this design rationale and to evaluate the usage. This case study showed that sDR provides concrete guidance (1) to derive robot functions and behaviors from the theory and (2) to designate the corresponding effects with evaluation instruments. Furthermore, it helps to establish an effective, incremental and iterative, design and evaluation process, by relating positive and negative evaluation outcomes to robot behaviors at the task and communication level. The proposed solution for explicating the design rationale makes it possible for others to understand the decisions made and thereby supports replicating experiments or reusing parts of the design rationale.

Objective: To assess the effects of a personal robot, providing diabetes self-management education in a clinical setting on the pleasure, engagement and motivation to play a diabetes quiz of children (7-12) with type 1 diabetes mellitus (T1DM), and on their acquisition of knowledge about their illness.Methods: Children with T1DM (N=27) participated in a randomized controlled trial (RCT) in which they played a diabetes mellitus self-management education (DMSE) game, namely a diabetes quiz, with a personal or neutral robot on three occasions at the clinic, or were allocated to a control group (care as usual). Personalised robot behaviour was based on the self-determination theory (SDT), focusing on the children's needs for competence, relatedness and autonomy. The SDT determinants pleasure, motivation and diabetes knowledge were measured. Child-robot interaction was observed, including level of engagement.Results: Results showed an increase in diabetes knowledge in children allocated to the robot groups and not in those allocated to the control group (P=.001). After three sessions, children working with the personal robot scored higher for determinants of SDT than children with the neutral" robot (P=.02). They also found the robot to be more pleasurable (P=.04), they answered more quiz questions correctly (P=.02), and were more motivated to play a fourth time (P=.03).The analysis of audio/video recordings showed that in regard to engagement, children with the personal robot were more attentive to the robot, more social, and more positive (P<.05).Conclusion: The study showed how a personal robot that plays DMSE games and applies STD based strategies (i.e.,provides constructive feedback, acknowledges feelings and moods, encourages competition and builds a rapport) can help to improve health literacy in children in an pleasurable, engaging and motivating way. Using a robot in health care could contribute to self -management in children with a chronic disease and help them to cope with their illness. (C) 2017 Published by Elsevier Ltd.

For effective child education, playing games with a social robot should be motivating for a longer period of time. One aspect that can affect the motivation of a child is the difficulty of a game. The game should be perceived as challenging, while at the same time, the child should be confident to meet the challenge. We designed a user modelling module that adapts the difficulty of a game to the childs skill level, in order to provide children with the optimal challenge. This module applies a Bayesian rating method that estimates the childs skill and game items difficulty levels to personalise the game progress. In an experiment with 22 children (aged between 10 and 12years old), we tested whether the personalisation leads to a higher motivation to play with the robot. Although the personalised system did not challenge the participants optimally, this study shows that the Bayesian rating system is in principle able to measure the skill and performance of children in playing a game with a robot (even without accurate estimates of the difficulty of items). We outline multiple ways in which the rating method and module can be used to further personalise and enhance the child-robot interaction, other than adapting the difficulty of games (e.g. by adapting the dialogue and feedback).

Turning a robot into an effective team-player requires continuous adaptation during its lifecycle to human team-members, tasks, and the technological environment. This paper proposes a concept for human-robot team development over longer periods of time and discusses technological and operational implications. From an operational perspective, we discuss the types of adaptations to team behavior that are required in a military house search scenario. From a technological perspective, we explain how teamwork adaptations can be implemented using a teamwork module based on ontologies and policies. The approach is demonstrated in a virtual environment, in which humans and robots collaborate to find objects in a house search.

Children with type 1 diabetes mellitus (T1DM) have a need for social, cognitive and affective support for self-management. The PAL project develops a social robot and its avatar. The aim is to assist the child, health care professional and parents to jointly perform diabetes management. Diabetes camps are an important setting in which the PAL can support children with T1DM. The video 'Learning with Charlie' shows how different robot buddies and children interact in a camp setting and learn about T1DM through educative activities. Also, the robots offer socio-emotional support in a pleasurable and safe environment.

Conversation Fillers (CFs), such as ‘um’, ‘hmm’, and ‘ah’, may help to improve the human-robot interaction by smoothening the robot's responses. This paper presents the design and test of such CFs - alongside iconic pensive or acknowledging gestures - for Wizard of Oz (WoZ) controlled open-ended dialogues in child-robot interactions. A controlled experiment with 26 children showed that these CFs can improve the perceived speediness, aliveness, humanness, and likability of the robot, without decreasing perceptions of intelligence, trustworthiness, or autonomy.

Persistent progress in the self-management of their disease is important and challenging for children with diabetes. The European ALIZ-e project developed and tested a set of core functions for a social robot that may help to establish such progress. These functions were studied in different set-ups and with different groups of children (e.g. classmates at a school, or participants of a diabetes camp). This paper takes the lessons learned from these studies to design a general scenario for educational and enjoying child–robot activities during returning hospital visits. The resulting scenario entailed three sessions, each lasting almost one hour, with three educational child–robot activities (quiz, sorting game and video watching), two intervening child–robot interactions (small talk and walking), and specific tests to assess the children and their experiences. Seventeen children (age 6–10) participated in the evaluation of this scenario, which provided new insights of the combined social robot support in the real environment. Overall, the children, but also their parents and formal caregivers, showed positive experiences. Children enjoyed the variety of activities, built a relationship with the robot and had a small knowledge gain. Parents and hospital staff pointed out that the robot had positive effects on child’s mood and openness, which may be helpful for self-management. Based on the evaluation results, we derived five user profiles for further personalization of the robot, and general requirements for mediating the support of parents and caregivers.

Social robots have the potential to provide support in a number of practical domains, such as learning and behaviour change. This potential is particularly relevant for children, who have proven receptive to interactions with social robots. To reach learning and therapeutic goals, a number of issues need to be investigated, notably the design of an effective child-robot interaction (cHRI) to ensure the child remains engaged in the relationship and that educational goals are met. Typically, current cHRI research experiments focus on a single type of interaction activity (e.g. a game). However, these can suffer from a lack of adaptation to the child, or from an increasingly repetitive nature of the activity and interaction. In this paper, we motivate and propose a practicable solution to this issue: an adaptive robot able to switch between multiple activities within single interactions. We describe a system that embodies this idea, and present a case study in which diabetic children collaboratively learn with the robot about various aspects of managing their condition. We demonstrate the ability of our system to induce a varied interaction and show the potential of this approach both as an educational tool and as a research method for long-term cHRI.

Eind 2015 zijn er problemen opgetreden met de performance van de infrastructuur van de huidige voorzieningen voor doven en slechthorenden om een beroep te doen op spoedeisende hulp (1-1-2). Deze problemen zijn inmiddels opgelost. Het ministerie van Veiligheid & Justitie (VenJ) heeft TNO desondanks gevraagd hen te adviseren over eventuele verbetermogelijkheden van het huidige stelsel. Dit rapport beschrijft de opzet en resultaten van dit project, wat heeft plaatsgevonden gedurende 5 weken (van 12 oktober tot 13 november 2015). In het rapport zijn de reacties van het ministerie op de conceptversie verwerkt. Wij hebben een aanpak in vier stappen gehanteerd: 1. Orientatie: creeren van een goed begrip van de behoeften door documentatie te bestuderen en gesprekken te voeren met betrokkenen vanuit het perspectief van gebruikers, proces en techniek; 2. Exploratie: bedenken van mogelijke oplossingsrichtingen, door middel van een workshop met TNO experts over gebruiker, proces, techniek en interactie-ontwerp; 3. Documentatie: verwoorden van de resultaten en het advies; 4. Presentatie: presenteren van het advies. Het project heeft een tiental voorstellen opgeleverd voor oplossingsrichtingen op de korte termijn: drie verbeteringen van de huidige situatie, twee 'Total Conversation standaard' oplossingen, twee 'Short Message Service' oplossingen, een 'social media' oplossing en twee 'telecom service' oplossingen. Bij elke oplossing wordt middels de visualisatie duidelijk aangegeven wat de verschillen zijn met de huidige situatie. Daarnaast is een waardering van alle alternatieven gegeven met betrekking tot robuustheid, toegankelijkheid, gebruiksgemak en dialoog. Het advies van TNO aan het Ministerie van Veiligheid & Justitie bestaat uit twee korte termijn en twee langere termijn oplossingen. De korte termijn oplossing (paragraaf 4.1) is een voorziening op basis van de Total Conversation standaard met een fall back voorziening, die desgewenst in twee fasen ontwikkeld kan worden. De langere termijnoplossingen (paragraaf 4.2) handelen over het maximaliseren van toegankelijkheid en van robuustheid.

Despite its acknowledged benefits for health promotion, the full potential of persuasive technology is not (yet) reached in regard to usability, effectiveness, and reproducibility. It often lacks an effective combination of technical features and behavior change strategies. This paper presents a multidisciplinary approach, addressing both aspects. It builds on the frameworks of situated Cognitive Engineering and Intervention Mapping. The approach generates building blocks from theory originating from different relevant disciplines; it specifies change objectives and requirements, described in the context of use, for intervention (strategy) and interaction (technology); it evaluates process, effect and impact, whereby claims on interaction and intervention are validated. To cope with language barriers between developers from different disciplines, the approach is presented as a guideline, illustrated with a case study. This approach is expected to contribute to a sound design rationale, a broad reach and ongoing use of the technology, and larger results in regard to health promotion.

Social robots may comfort and support children who have to cope with chronic diseases like diabetes. In social interactions, it is important to be able to express recognizable emotions. Studies show that the iCat robot, with its humanoid facial features, has this capability. In this paper we look if a Nao robot, without humanoid facial features, but with a body and colored eyes is also able to express recognizable emotions. We compare the recognition rates of the emotions between the Nao and the iCat. First a set of bodily expressions of the Nao for five basic emotions (angry, fear, happy, sad, surprise) was created and evaluated. With a signal detection task, the best recognizable bodily expression for each emotion was chosen for the final set. Then, fourteen children between 8 and 9 years old interacted both with the Nao and iCat to recognize the emotions within context, in a story-telling session, and without context. These interactions were repeated one week later to study the learning effect. For both robots, recognition rates for the expressions were relatively high (between 68 and 99% accuracy). Only for the emotional state of sadness, the recognition was significantly higher for the iCat (95%) than for the Nao (68 %). The emotions shown within context had higher recognition rates than those without context and during the second interaction the emotion recognition was also significantly higher than during the first session for both robots. To conclude: we succeeded to design a set of well-recognized dynamic emotional expressions for a robot platform, the Nao, without facial features. These expressions were better recognized when placed in a context, and when shown a week later. This set provides useful ingredients of social robot dialogs with children.

Children with diabetes can benefit from keeping a diary, but seldom keep one. Within the European ALIZ-E project a robot companion is being developed that, among other things, will be able to support and motivate diabetic children to keep a diary. This paper discusses the study of a robot supporting the use of an online diary. Diabetic children kept an online diary for two weeks, both with and without remote support from the robot via webcam. The effect of the robot was studied on children's use of the diary and their relationship with the robot. Results show that children shared significantly more personal experiences in their diaries when they were interacting with the robot. Furthermore, they greatly enjoyed working with the robot and came to see it as a helpful and supportive friend.

This paper describes our experience in designing, developing and deploying systems for supporting human–robot teams during disaster response. It is based on R&D performed in the EU-funded project NIFTi. NIFTi aimed at building intelligent, collaborative robots that could work together with humans in exploring a disaster site, to make a situational assessment. To achieve this aim, NIFTi addressed key scientific design aspects in building up situation awareness in a human–robot team, developing systems using a user-centric methodology involving end users throughout the entire R&D cycle, and regularly deploying implemented systems under real-life circumstances for experimentation and testing. This has yielded substantial scientific advances in the state-of-the-art in robot mapping, robot autonomy for operating in harsh terrain, collaborative planning, and human–robot interaction. NIFTi deployed its system in actual disaster response activities in Northern Italy, in July 2012, aiding in structure damage assessment. Graphical Abstract