Search

A personalized human-robot interaction (HRI) can increase the acceptance of robots through positive effects on the user experience (UX), as well as the user’s attitude towards and perception of the robot. From an ethical perspective, however, personalized HRI poses certain risks with regard to autonomy and manipulation of the users. Taking the scenario of a personalized quizmaster robot as an example, this paper combines the user centered design of a personalized robot behavior with ethical design perspectives. Based on motivation strate gies of the robot quiz master, the paper assesses and generalizes which interaction behaviors may be ethically permissible and at the same time enjoyable, engaging and motivating. Balancing the two perspectives of UX and ethical design, we propose transferable recommendations for the design of personalized HRI based on the approach of cascading models of design.

To integrate social robots in real-life contexts, it is crucial that they are accepted by the users. Acceptance is not only related to the functionality of the robot but also strongly depends on how the user experiences the interaction. Established design principles from usability and user experience research can be applied to the realm of human–robot interaction, to design robot behavior for the comfort and well-being of the user. Focusing the design on these aspects alone, however, comes with certain ethical challenges, especially regarding the user’s privacy and autonomy. Based on an example scenario of human–robot interaction in elder care, this paper discusses how established design principles can be used in social robotic design. It then juxtaposes these with ethical considerations such as privacy and user autonomy. Combining user experience and ethical perspectives, we propose adjustments to the original design principles and canvass our own design recommendations for a positive and ethically acceptable social human–robot interaction design. In doing so, we show that positive user experience and ethical design may be sometimes at odds, but can be reconciled in many cases, if designers are willing to adjust and amend time-tested design principles.

Affect monitoring is being discussed as a novel strategy to make adaptive systems more user-oriented. Basic knowledge about oscillatory processes and functional connectivity underlying affect during naturalistic human&ndash, computer interactions (HCI) is, however, scarce. This study assessed local oscillatory power entrainment and distributed functional connectivity in a close-to-naturalistic HCI-paradigm. Sixteen participants interacted with a simulated assistance system which deliberately evoked positive (supporting goal-achievement) and negative (impeding goal-achievement) affective reactions. Electroencephalography (EEG) was used to examine the reactivity of the cortical system during the interaction by studying both event-related (de-)synchronization (ERD/ERS) and event-related functional coupling of cortical networks towards system-initiated assistance. Significantly higher &alpha, band and &beta, band ERD in centro-parietal and parieto-occipital regions and &beta, band ERD in bi-lateral fronto-central regions were observed during impeding system behavior. Supportive system behavior activated significantly higher &gamma, band ERS in bi-hemispheric parietal-occipital regions. This was accompanied by functional coupling of remote &beta, band and &gamma, band activity in the medial frontal, left fronto-central and parietal regions, respectively. Our findings identify oscillatory signatures of positive and negative affective processes as reactions to system-initiated assistance. The findings contribute to the development of EEG-based neuroadaptive assistance loops by suggesting a non-obtrusive method for monitoring affect in HCI.

Hypertrophic cardiomyopathy (HCM) is associated with adverse left ventricular (LV) remodeling causing dysfunction and malignant arrhythmias. Severely affected patients present with disease onset during childhood and sudden cardiac death risk (SCD) stratification is of the highest importance in this cohort. This study aimed to investigate genotype–phenotype association regarding clinical outcome and disease progression in pediatric onset HCM. Medical charts from forty-nine patients with pediatric HCM who had undergone genetic testing were reviewed for retrospective analysis. Demographic, clinical, transthoracic echocardiographic, electrocardiographic, long-term electrocardiogram, cardiopulmonary exercise test, cardiac magnetic resonance, and medication data were recorded. Childhood onset HCM was diagnosed in 29 males and 20 females. Median age at last follow-up was 18.7 years (range 2.6–51.7 years) with a median follow-up time since diagnosis of 8.5 years (range 0.2–38.0 years). Comparison of patients carrying mutations in distinct genes and comparison of genotype-negative with genotype-positive individuals, revealed no differences in functional classification, LV morphology, hypertrophy, systolic and diastolic function, fibrosis and cardiac medication. Patients with compound mutations had a significantly higher risk for major arrhythmic events than a single-mutation carrier. No association between affected genes and disease severity or progression was identified in this cohort.

Adopting a need-based approach can help companies to create products and services that are preferred by their customers and improve their well-being, thus providing a competitive advantage. To put need-based designs into practice, it would be interesting to know how innovative product and service ideas can address the needs of a specific target group in a specific business domain. This paper presents an approach for (a) identifying such target group-specific need sets based on an online survey and (b) integrating them into the company’s innovation processes as part of a Need-based Creativity Workshop. To illustrate and validate this approach, we present a case study that investigates varying need subsets for two different user groups of future banking products and services in France: adults with and without families. Our study shows that a different set of needs is important for each group and reflects upon the benefits and challenges of a target group-specific, need-based design approach to leverage a company’s potential for innovation.

HRI designers are faced with the task of creating robots that are easy and pleasant to use for the users. The growing body of research in human–robot interaction (HRI) is still mainly focused on technical aspects of the interaction. It lacks defined guidelines that describe how behavioral expressions for social robots need to be designed to promote high usability and positive user experience. To achieve this goal, we propose to apply the concept of design patterns to HRI. We present a design process that provides step-by-step guidance and methods for HRI designers to generate high quality behavioral patterns for social robots that can be used for different robots and use cases. To document the resulting patterns, we developed a documentation format that provides a clear, standardized structure to note down all relevant aspects of a pattern so that others can understand its design recommendations and apply them to their own robot and use cases. In the present paper, we demonstrate our pattern approach based on an example and describe how we arrived at a pattern language of 40 behavioral patterns that found the basis for future social robot design and related research activities.

Robots have been proposed as intelligent technology that can support the independent living and health of older adults. While significant advances are being made regarding hardware and intelligent software to support autonomous actions of robots, less emphasis has been put on designing robot behavior that is comprehensible and pleasant for older adults. However, good usability and user experience are crucial factors for acceptance and long-term use. One way to actively engage older adults in behavioral design for social robots is participatory design. The Modality Card Deck is proposed, a tool that helps to engage older adults in human-robot interaction design process and participate in design decision for robot behavior. The cards guide the users towards creating ideas for design solutions which are detailed enough to be implemented by interaction designers and software developers. This paper provides a detailed description of the Modality Card Deck and presents an evaluation of the tool in the scope of a case study. In the case study, the card deck was used in participatory design workshops with older adults to develop multi-modal robot behaviors for the Pepper robot and a quiz game application. After describing the procedure of the case study, the workshop results and learnings about working with the Modality Card Deck and older adults are presented.

Background: Right ventricular impairment (RVI) secondary to altered hemodynamics contributes to morbidity and mortality in adult patients after tetralogy of Fallot (TOF) repair. The goal of this study was to describe signaling pathways contributing to right ventricular (RV) remodeling by analyzing over lifetime alterations of RV gene expression in affected patients. Methods: RV tissue was collected at the time of cardiac surgery in 13 patients with a diagnosis of TOF. RNA was isolated and whole transcriptome sequencing was performed. Gene profiles were compared between a group of 6 adults with signs of RVI undergoing right ventricle to pulmonary artery conduit surgery and a group of 7 infants, undergoing TOF correction. Definition of RVI in adult patients was based on clinical symptoms, evidence of RV hypertrophy, dilation, dysfunction or elevated pressure on echocardiographic, cardiovascular magnetic resonance, or catheterization evaluation. Results: Median age was 34 years in RVI patients and 5 months in infants. Based on P adjusted value

In Human-Robot Interaction, personalization has been proposed as a strategy to increase acceptance for social robots. The present paper describes how behavioral design patterns can be used to tailor the interaction experience to the individual user's characteristics and needs. To demonstrate this approach, we designed a quiz game application for the MiRo robot. The robot acts as the quizmaster and shows different behaviors (coach-like/empathic vs. challenging/provocative) depending on the type of user who is playing the game (community-focused vs. competition-focused player). We describe the process of creating the two quizmaster personalities and related behavioral patterns as well as the technical background for integrating them with the interaction model for the quiz game. The result is a Wizard-of-Oz demonstration of the personalizable quiz game that is accompanied by an interactive video prototype remote for user studies and demo purposes.

Many companies are facing the task for radical innovations—totally new concepts and ideas for products and services, which are successful at the market. One major factor for success is a positive user experience. Thus, design teams need, and are challenged to integrate, an experience-centered perspective in their human-centered design processes. To support this, we propose adjusted versions of the well-established user research methods focus groups and cultural probes, in order to tailor them to the specific needs and focus of experience-based design, especially in the context of solving “wicked design problems”. The results are experience focus groups and experience probes, which augment the traditional methods with new structuring, materials, and tasks based on the three principles experience focus, creative visualization, and systematic guidance. We introduce and describe a two step-approach for applying these methods, as well as a case study that was conducted in cooperation with a company that illustrates how the methods can be applied to enable an experience-centered perspective on the topic of “families and digital life”. The case study demonstrates how the methods address the three principles they are based on. Post-study interviews with representatives of the company revealed valuable insights about their usefulness for practical user experience design.

It has been argued that people are more inclined to accept a robot in their daily lives and even their home, if they have the feeling that the robot's behavior and interaction style matches their characteristics, needs and abilities. The concept of personalization has been introduced in order to create such personal, tailored human-robot interactions (HRI). Personalizing HRI means that robot takes into account individual user characteristics and can adjust its behavior to the situation and the human interaction partner. Previous HRI research indicates that personalization can have positive effects on the user experience during HRI as well as the user's attitudes towards and perceptions of the robot. This workshop is aimed at discussing the value of and exchanging ideas about the concept of personalization for HRI design. More concretely, we want to explore tools, methods and processes for appropriate robot behavior design and interaction modelling for personalized HRI. The workshop uses interactive, creative activities inspired by design thinking and participatory design to promote collaboration and co-creation between the participants and to inspire new, innovative perspectives on personalized HRI.

Entertainment applications for robots are often based on voice interaction. In these scenarios, the robot is primarily used as a voice assistant with a physical body. We conducted a study to investigate whether the entertainment value of a robot during a game can be attributed to the experience of voice interaction alone, or whether it is related to the physical presence of a robot and its expressivity through gestures and movement. The study examined the user experience for three different set-ups of a quiz game (with voice assistant, robot without animation, and animated robot). The results indicate that the perceived hedonic quality increases with physical presence and movement of the robot. Pragmatic quality was not rated differently for the three game versions. Additional qualitative interviews suggest that it might be desirable to design not overly expressive, but meaningful robot behavior for entertainment applications, in order to promote both, hedonic and pragmatic experience.

Using speech as an effective communication modality in human-robot interaction (HRI) allows designers to implement conceptual metaphors as a linguistic device. Metaphors appear to instantiate psychological framing effects and can influence the user´s reasoning significantly. The present paper presents two consecutive studies that explore how metaphors can be used in speech output for social robots to deliberately influence the user's perception of their relationship with the robot. As a first step, metaphoric expressions for framing cooperation or delegation in HRI settings were identified in a workshop. Effects of those metaphors on people´s strategies for organizing tasks in human-robot collaboration were then evaluated in an online survey. We found that metaphors suitable for encouraging users to do a task together with a robot are metaphors like "partners on a journey" or "allies". In contrast, metaphors that can be used to encourage handing over the task to a robot are metaphors like "boss" or "ruler". Further research needs to test whether these metaphors also have an effect on users' actions in HRI settings.

(1) Background: In cardiomyopathies, identification of genetic variants is important for the correct diagnosis and impacts family cascade screening. A classification system was published by the American College of Medical Genetics and Genomics (ACMG) in 2015 to standardize variants’ classification. The aim of the study was to determine the rate of reclassification of previously identified variants in patients with childhood-onset cardiomyopathies. (2) Methods: Medical records of patients and their relatives were screened for clinical and genetic information at the Department of Congenital Heart Defects and Pediatric Cardiology, German Heart Center Munich. Patients without an identified genetic variant were excluded from further analyses. Previously reported variants were reevaluated by the ACMG criteria in November 2021. (3) Results: Data from 167 patients or relatives of patients with childhood-onset cardiomyopathy from 137 families were analyzed. In total, 45 different genetic variants were identified in 71 individuals. Classification changed in 29% (13/45) with the greatest shift in “variants of unknown significance” to “(likely) benign” (9/13). (4) Conclusions: In patients with childhood-onset cardiomyopathies, nearly a third of reported genetic variants change mostly to more benign classes upon reclassification. Given the impact on patient management and cascade screening, this finding underlines the importance of continuous genetic counseling and variant.

It has been shown that emotional expressiveness makes robots appear more lifelike and believable. However, the facial design of commercially available robots is currently often not sufficient to convey emotions. We developed five facial design variants for a humanoid robot which can be used to display basic emotions (happiness, anger, sadness, fear) using different cartoon-inspired design approaches. These design variants were put on the head of the Pepper robot in cartoon-style drawings and tested in a quantitative user study. The findings indicate that the design approach of presenting the eyes on a large display and omitting the mouth is best suited to convey emotions, especially happiness and anger. Future work will improve the designs for sadness and fear, develop new designs for additional emotions and further investigate the role of the mouth design for emotional expressiveness of the robot.

We present an update from 6 years of practical use of UX Concept Exploration, a method for user research and user-driven innovation. After a short overview of the method, the paper describes experiences and suggests modifications of the method, where appropriate. Finally, we discuss guidelines to make the method usable in environments with only little UX expertise and limited resources, like small and medium-sized enterprises (SMEs) usually face.

Autonomous driving provides new opportunities for the use of time during a car ride. One such important scenario is working. We conducted a neuroergonomical study to compare three configurations of a car interior (based on lighting, visual stimulation, sound) regarding their potential to support productive work. We assessed participants? concentration, performance and workload with subjective, behavioral and EEG measures while they carried out two different concentration tasks during simulated autonomous driving. Our results show that a configuration with a large-area, bright light with high blue components, and reduced visual and auditory stimuli promote performance, quality, efficiency, increased concentration and lower cognitive workload. Increased visual and auditory stimulation paired with linear, darker light with very few blue components resulted in lower performance, reduced subjective concentration, and higher cognitive workload, but did not differ from a normal car configuration. Our multi-method approach thus reveals possible car interior configurations for an ideal workspace.

Brain-based interaction is discussed as a strategy to make assistive technologies more user-oriented. We investigated whether aging influences discrimination of neuroelectrical signatures underlying affective user reactions to system-initiated assistance behavior. Electroencephalography was used to examine the reactivity of the cortical system for two different age groups during interaction with a system that induce positive and negative affective events by supporting or impeding goal achievement during a navigation task. We found that affect processing during the interaction task remains unaffected by natural cortical alteration processes, but varied to different degrees across cortical regions between the two age groups. More specifically, discrimination based on P300 correlated with age, thus revealing a distinct intrinsic neurocognitive strategy in the aging brain. Addressing these neuroelectrical signatures may enable neuroadaptive assistance systems to perform user-specific adjustments.

To design successful, sustainable future mobility systems, it is crucial to provide incentives for commuters to change to eco-friendly alternative routes and means of transport. We believe that this can be realized by a user-centered, need-based design of a mobility infrastructure combined with an intelligent planning system that provides a positive commuting experience. As a first step towards this goal, we conducted interactive focus groups with commuters to identify their motivational drivers as well as opportunities for a positive, personalized commuting experience. The results reveal the demand to support the hedonic use of ways (taking routes for the enjoyable experience itself) and a segmentation into four mobility experience types (MxT) describing commuting and interaction preferences of commuters based on their need's profile.

User Experience research mainly makes use of self-reported measures to assess the user’s experience when using a technical product, especially regarding hedonic product qualities. Our study investigates whether pragmatic and hedonic qualities can be distinguished using two types of implicit measure: behavioural and neurophysiological. Participants interacted with two different software tools designed to emphasize hedonic and pragmatic qualities, respectively. Their implicit evaluations of the two prototypes were examined with the Approach Avoidance Task (AAT) and simultaneous electroencephalographic recordings (EEG), using snapshots from the interaction scenarios. While the AAT showed no differences, the analysis of event-related EEG potentials revealed differences around 300 ms after stimulus presentation. Significant higher cortical activity in the frontal cortex was found for approach tendencies towards snapshots taken from the hedonic prototype interaction. Higher potentials in the parietal (motor) cortex were found for avoidance tendencies towards the pragmatic prototype. The findings show that hedonic and pragmatic user experience qualities can be distinguished based on neuroelectrical data.

Basic human needs are a valuable source for creating meaningful products. Hence, designing for a positive User Experience requires an extensive understanding of those. Instead of just analysing abstract data, designers should also gather implicit information based on their own perception to gain holistic insights on the users' emotional perspectives. Inevitably there exists an influence of the designers' individual perspective on the accumulated insights during user research activities. However, if the designers are aware of their own and multiple other perspectives on needs, there is a good chance that they value relevant observations in user research.The NEEDS PROFILE (NP) is an approach to sensitise for diverse human needs and their characteristics. As designers often tend to find basic needs abstract, the NP enables them to explore basic needs as vivid personifications and encourages them to engage in a creative and playful manner first. Then these insights are confronted in guided discussions in order to enable sustainable learning. Evaluation results are positive, but further investigation needs to be done on long-term effects.

One core challenge in the field of neuro-adaptive technology is the detection of the current mental user state. Existing experimental paradigms use established stimulus material (e.g. pictures) to induce affective user states and make them measurable. Since these paradigms lack ecological validity, there is a pressing need to design more interactive stimulus material that allows a reliably and systematical induction of different affective user states in more realistic scenarios. We present and empirically validate a new experimental paradigm featuring a simulated adaptive system that induces positive and negative affective user states through supporting or impeding goal achievement during a navigation task. Furthermore, we tested the feasibility of quantifying underlying neurophysiological processes of affective states by simultaneous investigations of electroencephalographic and functional near-infrared spectroscopic. These investigations further show the effectiveness of our paradigm in inducing different levels of affect and provides an indication of features of brain activity containing discriminative information, a proposal that warrants further investigation in a larger cohort of participants.

Building Ideas is a novel innovation approach to design interactive products that can evoke positive user experiences. The approach mainly relies on new ways to reflect and negotiate about emotional and implicit concerns and ideas in a tight collaboration between user and design team. This work explains the main principles of the Building Ideas approach. Moreover, it provides examples to illustrate how the approach is implemented in practice by systematic guidance and new methods of user experience design.

This paper explores how technology for older adults needs to be designed to enhance their subjective feeling of wellbeing, supporting independence and health. In experience interviews which consider aspects of Positive Design and User Experience we assess which elements contribute to a positive experience in the everyday life of older adults. First results show that most positive experiences revolve around other people (family & friends). In total, twelve experience categories were identified which can be grouped into the three experience themes "connecting with people", "expressing oneself" and "meeting a challenge".

User experience (UX) has become a key factor in interface design. Still, so far, no satisfying solution exists for measuring the emotional user experience (UX) during human-technology interaction (HTI) and linking them to design elements of the interface. Non-invasive brain imaging techniques are promising tools to assess the underlying causes and generation of emotional experiences in the brain. Against this background, especially functional near-infrared spectroscopy (fNIRS), a rather new and portable method, appears to have strong potential for measuring UX in real-world HTI settings. However, so far fNIRS has scarcely been used in emotion research. The present research evaluates the feasibility of using fNIRS to detect emotional user responses during HTI by comparing it to the well-established method of fMRI which, due to its set-up, is difficult to use in HTI context. Our feasibility study shows that fNIRS can detect brain activity patterns which are similar to those obtained using fMRI and can be used to distinguished positive and negative emotional reaction in an HTI context and displays brain activities which cannot be examined when fMRI is used. Future research should investigate whether similar results can be found when fNIRS is used in less controlled and more realistic HTI scenarios.

The present Ph. D. project explores possibilities to apply neurophysiological methods for affect detection during human-technology interaction (HTI). Portable neurophysio-logical methods such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) offer an objective, ecologically valid and rather convenient way to infer the user's affective state through the monitoring of brain activity. To identify neural signatures for positive and negative affective user reactions an empirical study is proposed. The experimental design of this study enables synchronous data acquisition for EEG, fNIRS and psychophysiological measurements while the user is interacting with an adaptive web-interface. During the interaction process positive and negative affective states are induced by system-generated adaptive actions which are either appropriate and helpful or inappropriate and impedimental. The findings of the empirical study shed light into the question whether EEG, fNIRS or a hybrid approach that combines the employed methods is most reliable for affect detection during HTI.

Our research explores possibilities to apply neurophysiological methods for real-time emotion detection during human-technology interaction. The present paper outlines our scientific approach, research plan and methodology.

Besides providing functional support, socially assistive robots can provide social support in the form of entertainment. Previous studies have shown that this type of social support improves elderly people’s well-being significantly. But it is still far from clear what underlying causes drive people’s judgment of entertainment value. Showing emotionally expressive behaviors seems to raise entertainment value, but what if these behaviors are not truly embodied, i.e., tied to processes in the environment? It would seem that it is important that expressive behaviors are tied to the proper events. In this study, we investigated whether multimodal behavioral patterns (i.e., combinations of gestures, eye LED patterns, and verbal expressions) based on the developments within a game aids the entertainment value. We chose a gaming situation where the robot plays Mastermind with a human, in which the robot could show no behavioral patterns, behavioral patterns tied to game progress, or randomly selected behavioral patterns from the same set. The behavioral patterns were designed to imitate four basic emotions (neutral, happy, angry, sad) in combination with five levels of surprise and five levels of confidence. In a pilot study we validated the correct interpretation of the behavioral patterns. The experimental setup was designed to collect information about which behaviors to choose. The results of our study confirmed that a robot playing games with people has entertainment value. The main technical contribution is the information we collected on the behaviors.