Filtered by themeBehaviour change9 papersclear ✕

Toward Changing Users behavior with Emotion-based Adaptive SystemsMina Alipour · 2023Interactive computer systems’ designers emphasize the importance of considering humans, their emotions, and behaviors as first-class entities. Emotions are integral parts of human nature, and ignor- ing that can lead the interactive systems to failure, low quality, or discomfort. User interfaces (UIs) are increasingly becoming adap- tive to users’ various characteristics, intending to improve users’ satisfaction, performance, and decisions. However, the previous approaches proposed for supervising such adaptations are not effec- tively adopted in real-life problems. This paper proposes the novel approach to adapting UIs to users’ emotions using Model-Free Re- inforcement Learning (MFRL). The approach aims to maximize applying the essential adaptations and minimize the unnecessary ones towards users’ task completion and satisfaction. We chose emergency evacuation training as a suitable evaluation domain since people experience intense emotions in potential danger. We performed experiments with a mobile application we developed that acts as a recommender system in emergency training. By taking contextual input of the users’ basic emotions from face recognition, the application intelligently adapts its UI to quickly lead people to safe areas while arousing target emotions. The research includes lit- erature analysis, surveys, and further adopting an iterative process in implementation and experimentation. The evaluation process confirms the efficiency and effectiveness of the MFRL in iterations, as well as compared to other possible UI adaptation techniques, i.e., rule-based and sequential adaptation.

UX of AI & PersonalizationResearch Papers

Artificial Intelligence-Based Human–Computer Interaction Technology Applied in Consumer Behavior Analysis and Experiential EducationYanmin Li · 2022Li Y, Zhong Z, Zhang F and Zhao X (2022) Artificial Intelligence-Based Human–Computer Interaction Technology Applied in Consumer Behavior Analysis and Experiential Education. Front. Psychol. 13:784311. doi: 10.3389/fpsyg.2022.784311 In the course of consumer behavior, it is necessary to study the relationship between the characteristics of psychological activities and the laws of behavior when consumers acquire and use products or services. With the development of the Internet and mobile terminals, electronic commerce (E-commerce) has become an important form of consumption for people. In order to conduct experiential education in E-commerce combined with consumer behavior, courses to understand consumer satisfaction. From the perspective of E-commerce companies, this study proposes to use artificial intelligence (AI) image recognition technology to recognize and analyze consumer facial expressions. First, it analyzes the way of human–computer interaction (HCI) in the context of E-commerce and obtains consumer satisfaction with the product through HCI technology. Then, a deep neural network (DNN) is used to predict the psychological behavior and consumer psychology of consumers to realize personalized product recommendations. In the course education of consumer behavior, it helps to understand consumer satisfaction and make a reasonable design. The experimental results show that consumers are highly satisfied with the products recommended by the system, and the degree of sanctification reaches 93.2%. It is found that the DNN model can learn consumer behavior rules during evaluation, and its prediction effect is increased by 10% compared with the traditional model, which confirms the effectiveness of the recommendation system under the DNN model. This study provides a reference for consumer psychological behavior analysis based on HCI in the context of AI, which is of great significance to help understand consumer satisfaction in consumer behavior education in the context of E-commerce.

UX of AI & PersonalizationResearch Papers

Physiology-based personalization of persuasive technology: a user modeling perspectiveSpelt · 2021Persuasive technology (PT) can assist in behavior change. PT systems often rely on user models, based on behavior and self-report data, to personalize their function- alities and thereby increase efficiency. This review paper shows how physiological measurements could be used to further improve user models for personalization of PT by means of bio-cybernetic loops and data-driven approaches. Furthermore, we outline the advantages of using physiological measures for personalization compared to self-report and behavior measurement. Additionally, we show how two types of physiological information—physiological states and physiological reactivity—can be relevant for PT adaptations. To illustrate this, we present a model with two types of physiology-based PT adaptations as part of a bio-cybernetic loop; state-based and reactivity-based. Next, we discuss the implications of physiology-aware PT for per- suasive design and theory. And lastly, because of the potential impact of such systems, we also consider important ethical implications of physiology-aware PT. B Hanne A. A. Spelt [hanne.spelt@philips.com](mailto:hanne.spelt@philips.com); [h.a.a.spelt@tue.nl](mailto:h.a.a.spelt@tue.nl) Joyce H. D. M. Westerink [joyce.westerink@philips.com](mailto:joyce.westerink@philips.com); [j.h.d.m.westerink@tue.nl](mailto:j.h.d.m.westerink@tue.nl) Lily Frank [l.e.frank@tue.nl](mailto:l.e.frank@tue.nl) Jaap Ham [j.r.c.ham@tue.nl](mailto:j.r.c.ham@tue.nl) Wijnand A. IJsselsteijn [w.a.ijsselsteijn@tue.nl](mailto:w.a.ijsselsteijn@tue.nl) 1 Digital Engagement, Cognition & Behavior Group, Philips Research, High Tech Campus 34, 5656 AE Eindhoven, The Netherlands 2 Human-Technology Interaction Group, Faculty Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Postbus 513, 5600 MB Eindhoven, The Netherlands 3 Philosophy & Ethics Group, Faculty Industrial Engineering & Innovation Sciences, Eindhoven University of Technology, Postbus 513, 5600 MB Eindhoven, The Netherlands 123 134 H. A. A. Spelt et al.

UX of AI & PersonalizationResearch Papers

Towards User-Centric Intervention Adaptiveness: Influencing Behavior-Context Based Healthy Lifestyle InterventionsReceived September · 2020In the era of digital well-being, smart gadgets are the unobtrusive sources of acquiring infor- mation. A variety of personalized wellness applications support self-quantification based recommendations to provide wellness status for achieving personalized targets. However, these applications are unable to promote the induction of new healthy habits and thus are not too much effective for long term as users tend to loose their interest. Thus, we have proposed a methodology for User-Centric Adaptive Intervention based on behavior change theory for maintaining end-users’ interest. The methodology consists of four steps: (1) quantification of behavior based on contributing factors governed by expert-driven rules; (2) behavior-context based mapping for the identification of behavior status of the user; (3) selection of appropriate way of intervention to get fruitful outcomes; and finally (4) feedback based evaluation on the basis of recorded activities and questionnaires for satisfaction. A comprehensive healthy behavior index- based quantification supports the machine learning-based prediction model for behavior-context mapping. Furthermore, the evaluation is performed through implicit and explicit feedback analysis along with the accuracy of the behavior-context prediction model through multiple scenarios to cover comprehensive situations. The ensemble classifier suggests the accuracy of 98.02% for the behavior-context prediction model, which is higher than the other classifiers. The gain in behavior change is drawn from implicit feedback, which depicts that behavior context-based methods have improved the adaptation in behavior at a steady pace for the long term. The explicit feedback from 99 end-users of wellness application based on the proposed methodology obtained Good and Desired status for widely used System Usability Score and AttrakDiff tools respectively. INDEX TERMS User behavior, behavior-context, lifestyle, lifelog monitoring, self-quantification, healthy behavior index, adaptive interventions.

UX of AI & PersonalizationResearch Papers

A survey of cyber‑physical system implementations of real‑time personalized interventionsRobert Steele · 2019Advances in sensor technology and machine learning as well as the widespread use of smartphones are shifting the focus of healthcare. Emerging paradigms such as cyber-physical systems (CPSs) make possible the transition from reactive to preventive care. CPSs can be implemented to achieve effective mobile health solutions and to provide sophisticated new mechanisms to monitor an individual’s state in real-time via the use of sensors and mobile devices. Despite the significant potential impact of such systems, their implementation poses a range of complex technical challenges. This article surveys the state-of-the-art in implementations of CPSs for real-time personalized interventions. A general three layer architecture which can be used to consider current implementations is first presented along with a description of its main components. We also propose a three level taxonomy in accordance with the system capabilities. Then, the principal technical challenges, human-machine interaction challenges and future directions are discussed. Fifteen of the state-of-the-art implementations are qualitatively evaluated in terms of sensor capabilities, just-in-time reaction, interruptibility, and adherence, among other characteristics. By reviewing the state-of-the-art of the systems that have been built to-date, the focus of the review is to summarize current technical challenges and future opportunities for both future CPS implementers and behavioral scientists designing CPS for personalized interventions.

UX of AI & PersonalizationResearch Papers

Persuasive strategies and emotional states: towards designing personalized and emotion-adaptive persuasive systems2023Persuasive strategies have been widely operationalized in systems or applications to motivate behaviour change across diverse domains. However, no empirical evidence exists on whether or not persuasive strategies lead to certain emotions to inform which strategies are most appropriate for delivering interventions that not only motivate users to perform target behaviour but also help to regulate their current emotional states. We conducted a large-scale study of 660 participants to investigate if and how individ- uals including those at different stages of change respond emotionally to persuasive strategiesandwhy.Specifically,weexaminedtherelationshipbetweenperceivedeffec- tiveness of individual strategies operationalized in a system and perceived emotional states for participants at different stages of behaviour change. Our findings estab- lished relations between perceived effectiveness of strategies and emotions elicited in individuals at distinct stages of change and that the perceived emotions vary across stages of change for different reasons. For example, the reward strategy is associated with positive emotion only (i.e. happiness) for individuals across distinct stages of change because it induces feelings of personal accomplishment, provides incentives that increase the urge to achieve more goals, and offers gamified experience. Other strategies are associated with mixed emotions. Our work links emotion theory with behaviour change theories and stages of change theory to develop practical guidelines for designing personalized and emotion-adaptive persuasive systems. B Oladapo Oyebode oladapo.oyebode@dal.ca Darren Steeves darren@jackhabbit.com Rita Orji rita.orji@dal.ca 1 Faculty of Computer Science, Dalhousie University, Halifax, NS B3H 1W5, Canada 2 School of Health and Human Performance, Dalhousie University, Halifax, NS B3H 4R2, Canada 123 1176 O. Oyebode et al.

Emotional DesignResearch Papers

SMARTPHONE FOR SELF-MANAGEMENT OF PSYCHOLOGICAL STRESS: A PRELIMINARY EVALUATION OF POSITIVE TECHNOLOGY APPSILVIA SERINO, PIETRO CIPRESSO et al. · 2014In recent years, there is growing interest in the use of advanced technologies for suppor- ting well-being. The aim of this study was to test the efficacy of Positive Technology, the first application for smartphone and tablet that exploits the potential of new technologies and wearable biosensors for the self-management of psychological stress. 68 users who performed guided rela- xation or biofeedback exercises for at least 120 seconds were included in the sample. The stress management exercises performed with the application were effective in reducing users’ psycholo- gical stress level. It is possible to note a significant decrease in the arousal, associated with a con- comitant increase in the hedonic valence after the stress management exercises. A decrease in heart rate values was observed, although it was not statistically significant. Although preliminary, overa- ll these data suggest that even a brief stress management exercise carried out on a mobile application might be useful to reduce psychological discomfort.

Emotional DesignResearch Papers

The Behaviour Change Wheel: a new method for characterising and designing behaviour change interventions2011Background: Improving the design and implementation of evidence-based practice depends on successful behaviour change interventions. This requires an appropriate method for characterising interventions and linking them to an analysis of the targeted behaviour. There exists a plethora of frameworks of behaviour change interventions, but it is not clear how well they serve this purpose. This paper evaluates these frameworks, and develops and evaluates a new framework aimed at overcoming their limitations. Methods: A systematic search of electronic databases and consultation with behaviour change experts were used to identify frameworks of behaviour change interventions. These were evaluated according to three criteria: comprehensiveness, coherence, and a clear link to an overarching model of behaviour. A new framework was developed to meet these criteria. The reliability with which it could be applied was examined in two domains of behaviour change: tobacco control and obesity. Results: Nineteen frameworks were identified covering nine intervention functions and seven policy categories that could enable those interventions. None of the frameworks reviewed covered the full range of intervention functions or policies, and only a minority met the criteria of coherence or linkage to a model of behaviour. At the centre of a proposed new framework is a ‘behaviour system’ involving three essential conditions: capability, opportunity, and motivation (what we term the ‘COM-B system’). This forms the hub of a ‘behaviour change wheel’ (BCW) around which are positioned the nine intervention functions aimed at addressing deficits in one or more of these conditions; around this are placed seven categories of policy that could enable those interventions to occur. The BCW was used reliably to characterise interventions within the English Department of Health’s 2010 tobacco control strategy and the National Institute of Health and Clinical Excellence’s guidance on reducing obesity. Conclusions: Interventions and policies to change behaviour can be usefully characterised by means of a BCW comprising: a ‘behaviour system’ at the hub, encircled by intervention functions and then by policy categories. Research is needed to establish how far the BCW can lead to more efficient design of effective interventions. Background Improving the implementation of evidence-based prac- tice and public health depends on behaviour change. Thus, behaviour change interventions are fundamental to

Emotional DesignResearch Papers

Behavioural Intervention Technology in UX Design: Conceptual Review, Synthesis, and Research DirectionYoungsoo Shin, Chajoong Kim et al. · 2021The notion of Behavioural Intervention Technologies (BITs) has received increasing attention from researchers and practitioners creating design and technology to support users' behavioural change processes. However, the value of consolidating previous findings to connect insightful research and practical design works and generating new knowledge on BITs has been under-recognized in the design community. To support researchers and practitioners who struggle with creating humancentred BITs to effectively induce changes in human behaviour, this paper investigates existing literature on BITs through a systematic literature review with 28 selected publications. From this literature review process, this paper proposes a structured synthesis of extant perspectives and approaches, offering an overarching perspective for effective applications of the BIT design approach. At the end of the paper, these findings are extended to discuss further research and implementations of design practices for changes in human behaviours.

HCI & Adaptive InterfacesResearch Papers