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Ontology design is an important process for structuring knowledge to be reused in different projects in the health domain. In this paper, we describe an ontology design for the collaborative knowledge building system ACKTUS to be used for developing personalized knowledge applications for different domains. Different foundational ontologies were compared with respect to selected criteria considered vital for the project, such as modularity and descriptiveness.

Supporting human actors in daily living activities for improving health and wellbeing is a fundamental goal for assistive technology. The personalisation of the support provided by assistive technology in the form of digital coaching requires user models that handle potentially conflicting goals and motives. The aim of this research is to extend a motivational model implemented in an assistive technology, into a multipurpose motivational model for the human actor who is to be supported, which can be translated into a multipurpose goal model for a team of assistive agents. A team of assistive agents is outlined with supplementary goals following the human’s different properties. A method for generating multipurpose arguments relating to different motives were developed, and implemented in a human-agent dialogue system. The results are exemplified based on a use case from an earlier pilot user study of the assistive technology. Future work includes user studies to validate the model.

This paper proposes a cognitive architecture of an intelligent agent that can have a dialogue with a human agent on health-related topics. This architecture consists of four main components, namely, the Belief Base, the Dialogue Manager, the Task Manager and the Plan Generator. Each component has sub-components that perform a set of tasks for the purpose to enable the agent to be enrolled in a dialogue. In this paper the particular sub-component of the Dialogue Manager, the Dialogue Strategy has been discussed in detail. A notion of scheme is introduced, which functions as a template with variables that are instantiated each time a state is entered. The agent’s dialogue strategy is implemented as a combination of the schemes and the state transitions that the agent makes in response to the human’s request. We used a combination of finite-state and agent-based dialogue strategies for dialogue management. This combined dialogue strategy enables a multi-topic dialogue between a human and an agent.

A common conversation between an older adult and a nurse about health-related issues includes topics such as troubles with sleep, reasons for walking around nighttime, pain conditions, etc. Such a dialogue can be regarded as a "natural" dialogue emerging from the participating agents' lines of thinking, their roles, needs and motives, while switching between topics as the dialogue unfolds. The purpose of this work is to define a generic conceptual model of purposeful human-agent dialogue activity including different types of argumentation dialogues, suitable for health-related topics. This is done based on analyses of a scenario, persona and models of human behaviour. The model will be shared between the human and the agent, allowing for adaptation to the human's reasoning, needs and motives.

A common conversation between an older adult and a nurse about health-related issues includes topics such as troubles with sleep, reasons for walking around nighttime, pain conditions, etc. This dialogue emerges from the participating human's lines of thinking, their roles, needs and motives, while switching between topics as the dialogue unfolds. This paper presents a dialogue system that enables a human to engage in a dialogue with a software agent to reason about health-related issues in a home environment. The purpose of this work is to conduct a pilot evaluation study of a prototype system for human-agent dialogues, which is built upon a set of semantic models and integrated in a web application designed for older adults. Focus of the study was to receive qualitative results regarding purpose and content of the agent-based dialogue system, and to evaluate a method for the agent to evaluate its behavior based on the human agent's perception of appropriateness of moves. The participants include five therapists and 11 older adults. The results show users' feedback on the purpose of dialogues and the appropriateness of dialogues presented to them during the interaction with the software agent.

A common conversation between an older adult and a nurse about health-related issues includes topics such as troubles with sleep, reasons for walking around nighttime, pain conditions, etc. Such a dialogue can be regarded as a "natural" dialogue emerging from the participating agents' lines of thinking, their roles, needs and motives, while switching between topics as the dialogue unfolds. The purpose of this work is to define a generic model of purposeful human-agent dialogues suitable for health-related topics. This is done based on analyses of scenarios, personas and models of human behavior. The results include four models, which need to be included in a software agent's belief base; i) a user model, ii) a model of the domain knowledge related to the topic of the dialogue, iii) an agent model, and iv) a dialogue activity model. The models were implemented into a prototype system for human-agent dialogues, which was evaluated by therapists and a group of older adults.

In recent years, the interest in developing personalised applications for home environment has grown since it has a wide reach in helping people in their daily activities. However, for our purposes the concept activities of daily living also need to include work and leisure activities not necessarily performed in home environments. In this article, we describe an ongoing effort to develop a generic framework for assessing ability and tailoring of support applications in the health domain. We also give an overview of the approaches that have been adopted for personalisation and user modelling to various application areas. Suggestions of future development are provided.

This research project aims at supporting workers in the mining and construction industries and older adults at home, in monitoring the risks of their daily work or living situation. A goal is to create awareness in the individual about risks and how to decrease risks. Methods and knowledge-based applications are developed, which synthesise knowledge about the user, the user’s activities, the environment and generic domain knowledge for the purpose of providing tailored support and advice to individuals. This knowledge is also what the user can relate to, interact with and control through different methods. In this paper we investigate different approaches to user control of intelligent environments and propose a dialogue-based method for user control.

The goal of this study is to develop a computer-interpretable model for activity detection and representation, based on existing informal models of how humans perform activity. Appropriate detection of purposeful human activity is an essential functionality of active assistive technology aiming at providing tailored support to individuals for improving activity performance and completion. The main contribution is the design of a model for detection and representation of human activities based on three categories of instruments, which is implemented as two generic and supplementary terminology models: an event ontology and a core ontology. The core ontology is extended for each new knowledge domain into a domain ontology. The model builds the base for personalization of services generated by the cooperative reasoning performed by a human collaborating with an intelligent and social software agent. Ongoing and future work includes user studies in the different application domains.

Social isolation and loneliness have become everyday concerns forpopulations all over the world as these factors are affecting both physical and mentalhealth in a negative way. Feelings of isolation and loneliness are increasinglyacknowledged as a health risk among older persons. ICTs have been recognized aseffective tools to combat social isolation among older people. The aim of this studywas to explore factors of significance when introducing a tablet-based systemproviding digital social activities for older persons with home care. Participants were17 persons, age 70 and older, who lived alone and had assistance from home care.This exploratory study used cross-sectional qualitative data analyzed throughthematic analysis. Three themes were generated: 1) lacking vocabulary related tothe context, 2) intuitive user interface may replace extensive instructions and 3)unwillingness to commit to a pre-defined measure of performance.

Social isolation and loneliness among older people is a growing problem with negative effects on physical and mental health. In co-creation with older adults individualized social activities were designed where older adults through computer mediated communication were able to participate in social activities without leaving their homes. Four types of activities were designed; outdoor activity, music event, visiting a friend and leisure activity. A participatory action research design was applied, where end users together with scientists from two research fields developed, tested and evaluated online participation in the activities. Usability and safety of the systems were major concerns among older adults. The evaluation pointed out that level of simplicity, usability and audio-video quality determined the level of satisfaction with the human interaction during the activity, thereby affecting the meaningfulness of the activity. The research presented in this paper constitutes the first step in a long-term research process aiming at developing a digital coaching system that gives older adults personalized support for increasing participation in meaningful social activities.

The focus of this ECCE 2017 panel is on digital technology in healthcare and elderly care. The discussion concerns the design of technology and the use of technology for health. 

Functional Status Information (FSI) describes physical and mental wellness at the whole-person level. It includes information on activity performance, social role participation, and environmental and personal factors that affect the well-being and quality of life. Collecting and analyzing this information is critical to address the needs for caring for an aging global population, and to provide effective care for individuals with chronic conditions, multi-morbidity, and disability. Personal knowledge graphs (PKGs) represent a suitable way for meaning in a complete and structured way all information related to people’s FSI and reasoning over them to build tailored coaching solutions supporting them in daily life for conducting a healthy living. In this paper, we present the development process related to the creation of a PKG by starting from the HeLiS ontology in order to enable the design of an AI-enabled system with the aim of increasing, within people, the self-awareness of their own functional status. In particular, we focus on the three modules extending the HeLiS ontology aiming to represent (i) enablers and (ii) barriers playing potential roles in improving (or deteriorating) own functional status and (iii) arguments driving the FSI collection process. Finally, we show how these modules have been instantiated into real-world scenarios.

Functional Status Information (FSI) describes physical and mental wellness at the whole-person level, and includes information on activity performance, social role participation, and environmental and personal factors that affect well-being and quality of life. Collecting and analyzing this information is critical to addressing the data needs in caring for aging global populations, and providing effective care for individuals with chronic conditions, multi-morbidity, and disability. In this paper, we present a first step towards the design of Al-enabled system increasing the self-awareness of own functional status. In particular, we focus on the underlying semantic layer of the such an Al-enabled system by presenting two modules extending the HeLiS ontology aiming (i) to represent barriers in improving own functional status and (ii) to support the conceptual representation of the arguments leading to the detection of such barriers. Finally, we show through a running example how these modules can be instantiated.

In this paper we discuss various software engineering aspects of guideline computerisation, both from domain oriented as well as technology driven points of view. The discussion includes case studies on pharmacological treatment of hypertension, diagnosis of dementia, and drug interactions.

Clinical knowledge building upon evidence-based medicine is typically represented in textual guidelines, thus providing a rather informal description from a logical point of view. Further, the context which provides utility of these guidelines is not specified in any detail with respect to workflow and underlying motivations for decision-making. In addition, the level of detail is mostly static in the sense that measurements and decision values are fixed and intended for specific user groups. There is thus a lack of flexibility which disables knowledge to be shifted coherently between user levels in the entire workflow and decision process. In this paper, we will discuss formalizations of the underlying logical structures of guidelines from the viewpoint of being represented appropriately at each user level. Further, to establish a formal correctness criterion, the shift from one level of representation to another is required to be morphic in the categorical sense. General logics [7] is the selected generalized, and categorical, framework for our approach to flexible guideline representation. Our medical scope is dementia differential diagnosis based on consensus guidelines [2], and we focus on types of cognitive disorders as a prerequisite for further diagnostic tasks.

Clinical knowledge building upon evidence-based medicine is typically represented in textual guidelines, thus providing a rather informal description from a logical point of view. Further, the context which provides utility of these guidelines is not specified in any detail with respect to workflow and underlying motivations for decision-making. In addition, the level of detail is mostly static in the sense that measurements and decision values are fixed and intended for specific user groups. There is thus a lack of flexibility which disables knowledge to be shifted coherently between user levels in the entire workflow and decision process. In this paper, we will discuss formalizations of the underlying logical structures of guidelines from the viewpoint of being represented appropriately at each user level. Further, to establish a formal correctness criterion, the shift from one level of representation to another is required to be morphic in the categorical sense. General logics [6] is the selected generalized, and categorical, framework for our approach to flexible guideline representation. Our medical scope is dementia differential diagnosis based on consensus guidelines [2], and we focus on types of cognitive disorders as a prerequisite for further diagnostic tasks.

Background: With the evolution of contemporary occupations mediated by digital technologies (DTs), there is a need for occupational therapists to develop and structure knowledge on how to support older adults’ engagement in occupations and social participation in a digitalised society.

Objective: The objective of this study is to explore how tailoring to support older adults’ engagement in DT-mediated occupations could be schematised.

Material and methods: The study employed a multiple case study methodology. There were nine cases, with each case involving an older adult undergoing a collaborative process to support engagement in DT-mediated occupations. The collaborative process was initiated through questionnaires, observations, and dialogues. Meetings and tailoring strategies were documented in fieldnotes and memos on tailoring, respectively. Semi-structured interviews concluded data collection. Cross-case synthesis was used in data analysis.

Results: The result is a proposed scheme for tailoring to support older adults’ engagement in digital technology-mediated occupations, wherein strategies undertaken in the collaborative processes were synthesised and described.

Conclusion and significance: The proposed scheme for tailoring could contribute to occupational therapists’ knowledge on how to support older adults’ engagement in contemporary occupations. Testing the model in various practice settings is recommended in order to enhance occupational therapy practice.

Social participation and digital engagement can contribute to health and well-being among older adults. Because of older adults’ decline in abilities, coupled withcomplex technology and its perceived insufficient relevance to daily life, there is a need to create and tailor social opportunities and services that are supported by digital technologies for older adults to continue participating in society. Thus, it becomes relevant to explore older adults’ perceptions about contexts surrounding their social participation in a digital society. This exploration used a qualitative research design with focus group interviews and qualitative content analysis. Eighteen older adults, aged 66-81 years, from rural communities in Northern Sweden, participated in this study. The analysis resulted in three categories: Experiencing conditions for social participation in a state of flux, Perceiving drawbacks of urbanization on social participation, Welcoming digital technology that facilitates daily and community living.These categories were encapsulated in the theme –The juxtaposition of narrowing offline social networks and expanding digital opportunities for social participation. The findings suggested that co-creating usable digitalized services and facilitating satisfactory use of digital technologies could support older adults’ social participation through activities that they find relevant in their lives, and subsequently, might enable them to live longer at home.

In this paper, we present an argument-based mechanism to generate hypotheses about belief-desire-intentions on dynamic and complex activities of a software agent. We propose to use a composed structure called activity as unit for agent deliberation analysis, maintaining actions, goals and observations of the world always situated into a context. Activity transformation produces changes in the knowledge base activity structure as well in the agent’s mental states. For example, in car driving as a changing activity, experienced and novice drivers have a different mental attitudes defining distinct deliberation processes with the same observations of the world. Using a framework for understanding activities in social sciences, we endow a software agent with the ability of deliberate, drawing conclusion about current and past events dealing with activity transformations. An argument-based deliberation is proposed which progressively reason about activity segments in a bottom-up manner. Activities are captured as extended logic programs and hypotheses are built using an answer-set programming approach. We present algorithms and an early-stage implementation of our argument-based deliberation process.

Theories about human activity and motivation point out that motives are driving forces behind human activities and development of healthy and unhealthy habits. Activity theory is one of these that has been applied to develop activity-centered user interfaces. Activity theory differentiates between sense-making and stimuli-oriented types of motives that have a strong influence on our daily behavior. Two main challenges are explored in this paper: 1) the personalisation of graphical user interfaces to mediate representations of motivation-based activities to support behaviour change processes; and 2) the proactiveness of such visual representations.

As methods, we use activity theory as a framework for defining the motivations' dynamics, and formal argumentation theory as the underlying mechanism for interactive reasoning and decision-making in the process of generating the user interface.

Our contributions are two-folded: 1) a dynamic graphical user interface where the background responds to behaviors linked to sense-making motives, and the foreground to stimuli motivation; and 2) a non-monotonic reasoning mechanism endowing the user interface with proactiveness (not only react to the user interactions but trigger and direct attention to potential conflicts), and a motive-based behavior conflict resolution process. Future work includes user studies to explore how triggering of focus may create increased awareness in an individual of conflicting motives in daily activities and how this may support changes of unhealthy habits.

Persuasion is an active research topic in artificial intelligence (AI), human-computer interaction (HCI), and social sciences. When persuasive technology has been designed, some HCI guidelines have commonly used disregarding the current AI state of the art, for example, ignoring autonomy and proactive AI behavior. In this paper, a systematic review of HCI persuasive strategies and their corresponding content is mapped to a formal AI approach using argumentation theory. We also present experimental results using as context a mobile application for behavior change in the Swedish context.

Intelligent Assistive Systems (IASs) provide personalised support to individuals to increase their autonomy and competence in performing activities. The personalisation of such technology represents a particular challenge, for the individuals abilities typically change over time. The aim of this research was to explore a theory-based, activity-centred framework for the development of IASs that both facilitate the active involvement of caregivers and target users and allow for adaptation to the individual over time.

Medication management was focused on as a case study. Three older adults and two caregivers were involved in a co-design process of an IAS prototype system, the MED-AR, which uses projection-based augmented reality as the user interface technology. The theoretical framework for the design and evaluation of the MED-AR was activity theory. For the decision-making process of the MED-AR, formal argumentation theory was used. The major contributions of the study are (i) a formal framework for understanding the level of independence in activities and the way an IAS can tailor support to an individual and a situation, including caregivers; and (ii) a model for involving older adults and caregivers in a co-design process in the first phases of developing IASs.

This paper is aimed at formalizing the interplay among a person to be assisted, an assistive agent-based software, and a caregiver. We propose principles that agents should follow in such interplay, this principles may have impact in different agent-based assistive technology. We propose a mechanism to integrate individual’s information into the final decision-making process of an agent. Moreover, we endow agents with mechanisms for evaluating the distance between independent and supported activity execution, the so called zone of proximal development (ZPD) in four scenarios: I) independent activity execution by a person; II) ZPDH activity performance of a person supported by another person (e.g. a therapist); III) the ZPDS representing a potential activities when a person is supported by a software agent; and IV) the ZPDH+S when a person is supported by a caregiver and a software agent. Formal argumentation theory is used as foundation. Our formal models were tested using a prototype using augmented reality as assistive software. A pilot study with older adults and health-care personnel was performed and formal and empirical results are presented.

We introduce the Assisted Living system ALI, which is a novel approach to providing assistance and support in activities of daily life. We integrate a human behavior theory with a default reasoning decision making framework. This integration allows us to model a decision making problem from a human activity centric point of view and at the same time, formalize these elements using a possibilistic argumentation theory. ALI sends personalized notifications suggesting the most suitable activities to perform and determines what activities were performed during a time period.

We introduce the Assisted Living system ALI, which is a novel approach to providing assistance and support in activities of daily life. We integrate a human behavior theory with a default reasoning decision making framework. This integration allows us to model a decision making problem from a human activity centric point of view and at the same time, formalize these elements using a possibilistic argumentation theory. ALI sends personalized notifications suggesting the most suitable activities to perform and determines what activities were performed during a time period.

Tailoring assistive systems for guiding and monitoring an individual in daily living activities is a complex task. This paper presents ALI, an assistive system combining a formal possibilistic argumentation system and an informal model of human activity: the Cultural-Historic Activity Theory, facilitating the delivery of tailored advices to a human actor. We follow an activity-centric approach, taking into consideration the human’s motives, goals and prioritized actions. ALI tracks a person in order to I) determine what activities were performed over a period of time (activity recognition tracking), and II) send personalized notifications suggesting the most suitable activities to perform (decision-making monitoring). The ALI system was evaluated in a formative pilot study related to promote social activities and physical exercise.

In this paper, we introduce an argumentation approach which takes an extended logic program as input and gives a set of arguments with the respective disagreements among them as output. We establish the notion of an argument under the Well-Founded semantics and Stable semantics inferences, allowing us to identify arguments with stratified programs as support, even when the input for the argument engine is a non-stratified program. We propose a set of rationality postulates for argument-based systems under extended logic programs, which are based on a definition of closure for a set of clauses that consider the well-known Gelfond-Lifschitz reduction. We establish the conditions under which our approach satisfies these principles. In addition, we present a standalone argumentation-tool based on the XSB system which implements our argumentation approach.

Theoretical frameworks have been developed for enabling software agents to evaluate simple activities such as walking and sitting. However, such frameworks typically do not include methods for how practically dealing with uncertain sensor information. We developed an argument-based method for evaluating complex goal-based activities by adapting two qualifiers: Performance and Capacity defined in the health domain. The first one evaluates what a person does, and the second one how "well" or "bad" an activity is executed. Our aim is to deal with uncertainty and inconsistent information; generate consistent hypotheses about the activity execution; and resemble an expert therapist judgment, where an initial hypothesis assessment can be retracted under new evidence. We conducted a pilot test in order to evaluate our approach using a Physiotherapy assessment test as a goal-based activity. Results show that skeptic argumentation semantics are may be useful for discriminating individuals without physical issues by considering Performance and Capacity; conversely, credulous semantics may be suitable for obtaining information in the evaluation of activity, which an intelligent agent may use for providing personalized assistance in an ambient assisted living environment.

Based on an argumentation theory approach, we present a novel method for evaluating complex goal-based activities by generalizing a notion of qualifier defined in the health domain. Three instances of the general qualifier are proposed: Performance, Actuation and Capacity; the first one evaluates what a person does, the second how an individual follows an action plan, and the third one how "well" or "bad" an activity is executed. Qualifiers are intended to be used by autonomous systems for evaluating human activity. We exemplify our approach using a health domain assessment protocol. Main results of this test show a partial correlation between ambiguities assessed by experts and our argument-based approach; and a multi-dimensional perspective how an activity is executed when a combined evaluation of qualifiers is used. This last outcome was interesting for some therapists consulted. Results also show differences between values of qualifiers using different argumentation semantics; two scenarios were proposed by therapist for using different semantics: preliminary activity screening and time-span follow-up evaluation.

Background and Objective: When agents (e.g. a person and a social robot) perform a joint activity to achieve a joint goal, they require sharing a relevant group intention, which has been defined as a We-intention. In forming We-intentions, breakdown situations due to conflicts between internal and “external” intentions are unavoidable, particularly in healthcare scenarios. To study such We-intention formation and “reparation” of conflicts, this paper has a two-fold objective: introduce a general computational mechanism allowing We-intention formation and reparation in interactions between a social robot and a person; and exemplify how the formal framework can be applied to facilitate interaction between a person and a social robot for healthcare scenarios.

Method: The formal computational framework for managing We-intentions was defined in terms of Answer set programming and a Belief-Desire-Intention control loop. We exemplify the formal framework based on earlier theory-based user studies consisting of human-robot dialogue scenarios conducted in a Wizard of Oz setup, video-recorded and evaluated with 20 participants. Data was collected through semi-structured interviews, which were analyzed qualitatively using thematic analysis. N=20 participants (women n=12, men=8, age range 23-72) were part of the study. Two age groups were established for the analysis: younger participants (ages 23-40) and older participants (ages 41-72).

Results: We proved four theoretical propositions, which are well-desired characteristics of any rational social robot. In our study, most participants suggested that people were the cause of breakdown situations. Over half of the young participants perceived the social robot's avoidant behavior in the scenarios.

Conclusions: This work covered in depth the challenge of aligning the intentions of two agents (for example, in a person-robot interaction) when they try to achieve a joint goal. Our framework provides a novel formalization of the We-intentions theory from social science. The framework is supported by formal properties proving that our computational mechanism generates consistent potential plans. At the same time, the agent can handle incomplete and inconsistent intentions shared by another agent (for example, a person). Finally, our qualitative results suggested that this approach could provide an acceptable level of action/intention agreement generation and reparation from a person-centric perspective.

This paper is aimed at formalizing the interplay among a person to be assisted, an assistive agent-based software, and a caregiver. We propose general principles for designing the interplay between a person to be assisted and an agent based on formal argumentation theory to characterize the agent’s reasoning processes. These principles emerge from a novel perspective to understand assistive technology using the concept of zone of proximal development (ZPD) from social sciences. ZPD can be understood as a measurement of activity development, comparing what a person can perform with or without external help. We characterize a rational agent in four ZPD zones: (I) independent activity execution, agent takes no action; (II) ZPD_H: a person supported by another person, agent takes no action; (III) ZPD_S: a person is supported by an agent; and (IV) ZPD_H+S: a person is supported by a caregiver and a software agent at the same time. An algorithm was developed for the agent to reason about the actions to be selected in different situations, based on formal argumentation theory for allowing non-monotonic reasoning. The formal models and algorithm were implemented in a prototype system using augmented reality as interface. Future work includes evaluating the principles and algorithm in actual use situations.

The aim of this research is to conduct a pilot study of a prototype that provides feedback using theory-based motivating messages developed by older adults, in a context of every day activities that include both physical and social activities. The prototype mobile application integrated the messages, a motivational model, and a personalization module that selects motivational messages based on preferences, motivational profile and the situation. The four participating older adults used the application for planning and following up social and physical activities. They found the messages entertaining and appreciated the dialogues with the application. They used the dialogues primarily to reinforce their satisfaction regarding conducted activities and did not necessarily tell the truth about conduced activities in the interaction with the application. The results are preliminary, but give valuable implications for further development of the personalisation module towards more purposeful use of ambient information, and aspects to explore in future user studies.

A methodology was defined and developed for designing theory-based behaviour change systems for health promotion that can be tailored to the individual. Theories from two research fields were combined with a participatory action research methodology. Two case studies applying the methodology were conducted. During and between group sessions the participants created material and designs following the behaviour change strategy themes, which were discussed, analysed and transformed into a design of a behaviour change system. Theories in behavioural change and persuasive technology guided the data collection, data analyses, and the design of a behaviour change system. The methodology has strong emphasis on the target group's participation in the design process. The different aspects brought forward related to behaviour change strategies defined in literature on persuasive technology, and the dynamics of these are associated to needs and motivation defined in literature on behaviour change. It was concluded that the methodology aids the integration of theories into a participatory action research design process, and aids the analyses and motivations of design choices.

The aim is to develop an adaptive computer-based intervention that gives seniors personalized support for increasing physical and social activity. The user-centered studies have been conducted. The results indicate that the seniors need to be categorized based on their preferences regarding a sub-set of messages.

Background: Despite the significant value of physical activity for the health of older adults, this population often fails to achieve recommended activity levels. Digital interventions show promise in providing support for self-managed physical activity. However, more information is needed about older adults' preferences for digital support to change physical activity behaviors as well as the process of designing them. The aim of this paper was to describe the participatory design process in which older adults were involved in the co-creation of digitally supported behavioral change strategies to support self-managed physical activity, and how the results were integrated in a prototype.

Methods: The participatory design process involved with nine older adults and two researchers. The participants were divided in two groups, and each group participated in three workshops and completed home tasks in between workshops. Following an iterative design process influenced by theories of behavior change, the workshops and home tasks were continuously analyzed, and the content and process were developed between groups and the next set of workshops. Prototypes of a mobile health (mHealth) solution for fall preventive exercise for older adults were developed in which the conceptualized strategies were integrated. To support coherence in reporting and evaluation, the developed techniques were mapped to the Behavior Change Technique Taxonomy v1 and the basic human psychosocial needs according to the Self-determination Theory.

Results: The results highlight different preferences of older adults for feedback on physical activity performance, as well as the importance of transparency regarding the identification of the sender of feedback. Preferences for content and wording of feedback varied greatly. Subsequently, the design process resulted in a virtual health coach with three different motivational profiles and tools for goal setting and self-monitoring. These behavior change strategies were integrated in the exercise application Safe Step v1. The conformity of the design concepts with the needs of Self-determination Theory and Behavior Change Technique Taxonomy v1 are presented.

Conclusion: The participatory design process exemplifies how older adults successfully contributed to the design of theory-based digital behavior change support, from idea to finished solution. Tailoring feedback with a transparent sender is important to support and not undermine motivation.

The purpose of this research is to explore how an intelligent digital companion (agent) can support persons (human) with stress-related exhaustion to manage daily activities. In this paper, we explore in particular how information about a person's emotions can be communicated to the agent with means of non-verbal communication through tangible interfaces. The purpose is to explore how different individuals approach the task of designing their own tangible interfaces for communicating emotions with a digital companion, and the range of different preferences and expectations. Six participants were interviewed and created tangible prototypes during a co-creation workshop. The data was analysed using theories about human emotions and activity, and translated into a generic user model, an architecture for a multiagent system and interface design proposals. The results include increased understanding of how different individuals would like to express their emotions with tangible interfaces, and informed the design of the information models regarding representing emotions. The study illuminated the importance of personalisation of functionality and interface design to address the diversity among individuals, as well as the design of the adaptive behaviour of a digital companion. Future work includes further studies involving additional participants, the development of the stress management application and conducting user studies where prototypes are used in daily activities.

Participating in social activities promotes healthy ageing, whereas loneliness and isolation are known to cause adverse effects on both physical and mental wellbeing. Technology that exists in society today can facilitate healthy ageing. However, a gap can be seen between seniors and technology in today's internet and communication technological device's user interfaces. Due to limited prior knowledge of interacting with touch screen devices, seniors sometimes have difficulties using them. This research aims to explore the user interfaces and their elements designed using a human-centered design methodology by involving seniors as activate participants in the design process. This work's outcome can improve current user interface design practices in touch screen devices, which might be seen as contributing step to understand the gap between seniors and technology.

For agent-based social simulations to be a powerful tool for policy makers and other decision makers in a given context (e.g. the current COVID-19 pandemic), they need to be socially realistic and thus, appropriately represent complex social concepts, such as social rules. In this paper, we focus on norms. Norms describe ‘normal’ behavior and aim at assuring the interests and values of groups or the society as a whole. People react differently to norms, and focus only on the parts that are relevant for them. Furthermore, norms are not only restrictions on behavior, but also trigger new behavior. Seeing a norm only as a restriction on certain behavior misses important aspects and leads to simulations that can be very misleading. Different perspectives need to be incorporated into the simulation to capture the variety of ways different stakeholders react to a norm and how this affects their interaction. We therefore present an approach to include these different perspectives on norms, and their consequences for different people and groups in decision support simulations. A perspective is specified by their goals, actions, effects of those actions, priorities in values, and social affordances. Through modeling perspectives we enable policy makers and other decision makers (the users) to be active in the modeling process and to tailor the simulation to their specific needs, by representing norms as modifiable objects, and providing textual and graphical representations of norms. This provides them with differentiated insights meaningful for the decisions they are faced with. We indicate the requirements for both the simulation platform as well as the agents that follow from our approach. Early explorations of our social simulation are showing the necessity of our approach.

Technologies that shape human behavior are of high societal relevance, both when considering their current impact and their future potential. In information systems research and in behavioral psychology, such technologies are typically referred to as persuasive technologies. Traditional definitions like the ones created by Fogg, and Harjumaa and Oinas-Kukkonen, respectively, limit the scope of persuasive technology to non-coercive, non-deceptive technologies that are explicitly designed for persuasion. In this paper we analyze existing technologies that blur the line between persuasion, deception,and coercion. Based on the insights of the analysis, we lay down an updated definition of persuasive technologies that includes coercive and deceptive forms of persuasion. Our definition also accounts for persuasive functionality that was not designed by the technology developers. We argue that this definition will help highlight ethical and societal challenges related to technologies that shape human behavior and encourage research that solves problems with technology-driven persuasion. Finally, we suggest multidisciplinary research that can help address the challenges our definition implies. The suggestions we provide range from empirical studies to multi-agent system theory.

Identifying and resolving conflicts of interests is a key challenge when designing autonomous agents. For example, such conflicts often occur when complex information systems interact persuasively with humans and are in the future likely to arise in non-human agent-to-agent interaction. We introduce a theoretical framework for an empathic autonomous agent that proactively identifies potential conflicts of interests in interactions with other agents (and humans) by considering their utility functions and comparing them with its own preferences using a system of shared values to find a solution all agents consider acceptable. To illustrate how empathic autonomous agents work, we provide running examples and a simple prototype implementation in a general-purpose programing language. To give a high-level overview of our work, we propose a reasoning-loop architecture for our empathic agent.

Typically, humans do not act purely rationally in the sense of classic economic theory. Different patterns of human actions have been identified that are not aligned with the traditional view of human actors as rational agents that act to maximize their own utility function. For instance, humans often act sympathetically -- i.e., they choose actions that serve others in disregard of their egoistic preferences. Even if there is no immediate benefit resulting from a sympathetic action, it can be beneficial for the executing individual in the long run. This paper builds upon the premise that it can be beneficial to design autonomous agents that employ sympathetic actions in a similar manner as humans do. We create a taxonomy of sympathetic actions, that reflects different goal types an agent can have to act sympathetically. To ensure that the sympathetic actions are recognized as such, we propose different explanation approaches autonomous agents may use. In this context, we focus on human-agent interaction scenarios. As a first step towards an empirical evaluation, we conduct a preliminary human-robot interaction study that investigates the effect of explanations of (somewhat) sympathetic robot actions on the human participants of human-robot ultimatum games. While the study does not provide statistically significant findings (but notable differences), it can inform future in-depth empirical evaluations.

In a previous publication, we introduced the core concepts of empathic agents as agents that use a combination of utility-based and rule-based approaches to resolve conflicts when interacting with other agents in their environment. In this work, we implement proof-of-concept prototypes of empathic agents with the multi-agent systems development framework Jason and apply argumentation theory to extend the previously introduced concepts to account for inconsistencies between the beliefs of different agents. We then analyze the feasibility of different admissible set-based argumentation semantics to resolve these inconsistencies. As a result of the analysis we identify the maximal ideal extension as the most feasible argumentation semantics for the problem in focus.

Identifying and resolving conflicts of interests is a key challenge when designing autonomous agents. For example, such conflicts often occur when complex information systems interact persuasively with humans and are in the future likely to arise in non-human agent-to-agent interaction. We work towards a theoretical framework for an empathic autonomous agent that proactively identifies potential conflicts of interests in interactions with other agents (and humans) byl earning their utility functions and comparing them with its own preferences using a system of shared values to find a solution all agents consider acceptable.To provide a high-level overview of our work, we propose a reasoning-loop architecture to address the problem in focus. To realize specific components of the architecture, we suggest applying existing concepts in argumentation and utility theory. Reinforcement learning methods can be used by the agent to learn from and interact with its environment.

This article presents an empirical requirement elicitation study for an argumentation-based digital companion for supporting behavior change, whose ultimate goal is the promotion and facilitation of healthy behavior. The study was conducted with non-expert users as well as with health experts and was in part supported by the development of prototypes. It focuses on human-centric aspects, in particular user motivations, as well as on expectations and perceptions regarding the role and interaction behavior of a digital companion. Based on the results of the study, a framework for person tailoring the agent's roles and behaviors, and argumentation schemes are proposed. The results indicate that the extent to which a digital companion argumentatively challenges or supports a user's attitudes and chosen behavior and how assertive and provocative the companion is may have a substantial and individualized effect on user acceptance, as well as on the effects of interacting with the digital companion. More broadly, the results shed some initial light on the perception of users and domain experts of “soft,” meta-level aspects of argumentative dialogue, indicating potential for future research.