Till Nagel

Regulated healthcare settings continue to face gaps between established HCI methodology, user-centered design principles, and everyday clinical practice. Although standards and regulatory frameworks mandate usability engineering, their integration into regulated clinical settings often remains inconsistent, compliance-driven, and detached from real-world workflows. To better understand and address this disconnect, we report insights from applied work in clinical studies, hospital collaborations, and industry partnerships. Our aim is to identify methodological and organizational challenges in assessing digital health technologies and discuss potential strategies to mitigate them. While usability evaluations are typically conducted in accordance with international standards, our observations reveal systemic problems: hospital stakeholders are rarely involved in early design stages, procurement decisions are frequently made without structured user testing, and patients are often excluded from technology selection processes. We argue that usability engineering should be a formative, safety-critical discipline integrated throughout the product lifecycle, including aftermarket deployment, and not merely a compliance task. Drawing on case study reflections and practitioner experience, we articulate actionable lessons and practical strategies for integrating usability engineering more effectively into regulated healthcare environments. By bridging methodological, regulatory, and organizational divides, the paper contributes to guidance for aligning human-centered design with the needs of complex healthcare systems.

This paper presents the Urban Data Visualization (UDV) card deck, a tool designed to facilitate reflective discussions and inform the collaborative design process of urban data visualizations. The UDV card deck was developed to bridge the gap between theoretical knowledge and practice in workshop settings, fostering inclusive and reflective approaches to visualization design. Drawing from urban visualization design literature and the results from a series of expert workshops, these cards summarize key considerations when designing urban data visualizations. The card deck guides different activities in an engaging, collaborative, and structured format, promoting inclusion of diverse urban actors. We introduce the card deck and its goals, demonstrate its use in four case studies, and discuss our findings. Feedback from workshop participants indicates that the UDV card deck can serve as a supportive and reflective tool for urban data visualization researchers, designers and practitioners.

Objectives: Medical practitioners analyze numerous types of data, often using archaic representations that do not meet their needs. Pneumologists who analyze lung function exams must often consult multiple exam records manually, making comparisons cumbersome. Such shortcomings can be addressed with interactive visualizations, but these must be designed carefully with practitioners’ needs in mind. Materials and Methods: A workshop with experts was conducted to gather user requirements and common tasks. Based on the workshop results, we iteratively designed a web-based prototype, continuously consulting experts along the way. The resulting application was evaluated in a formative study via expert interviews with 3 medical practitioners. Results: Participants in our study were able to solve all tasks in accordance with experts’ expectations and generally viewed our system positively, though there were some usability and utility issues in the initial prototype. An improved version of our system solves these issues and includes additional customization functionalities. Discussion: The study results showed that participants were able to use our system effectively to solve domain-relevant tasks, even though some shortcomings could be observed. Using a different framework with more fine-grained control over interactions and visual elements, we implemented design changes in an improved version of our prototype that needs to be evaluated in future work. Conclusion: Employing a user-centered design approach, we developed a visual analytics system for lung function data that allows medical practitioners to more easily analyze the progression of several key parameters over time.

Background: Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users’ acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential. Objective: This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations. Methods: We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords “wearable devices,” “mobile apps,” “mHealth apps,” “physiological data,” “usability,” “user experience,” and “user evaluation” were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. Results: A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50%), ease of use (27/68, 40%), user experience (16/68, 24%), perceived usefulness (18/68, 26%), and effectiveness (15/68, 22%). Only 10% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation. Conclusions: Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations.

BACKGROUND Wearable devices, mobile technologies, and their combination have been accepted into clinical use to better assess the physical fitness and quality of life of patients and as preventive measures. Usability is pivotal for overcoming constraints and gaining users’ acceptance of technology such as wearables and their companion mobile health (mHealth) apps. However, owing to limitations in design and evaluation, interactive wearables and mHealth apps have often been restricted from their full potential. OBJECTIVE This study aims to identify studies that have incorporated wearable devices and determine their frequency of use in conjunction with mHealth apps or their combination. Specifically, this study aims to understand the attributes and evaluation techniques used to evaluate usability in the health care domain for these technologies and their combinations. METHODS We conducted an extensive search across 4 electronic databases, spanning the last 30 years up to December 2021. Studies including the keywords “wearable devices,” “mobile apps,” “mHealth apps,” “physiological data,” “usability,” “user experience,” and “user evaluation” were considered for inclusion. A team of 5 reviewers screened the collected publications and charted the features based on the research questions. Subsequently, we categorized these characteristics following existing usability and wearable taxonomies. We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. RESULTS A total of 382 reports were identified from the search strategy, and 68 articles were included. Most of the studies (57/68, 84%) involved the simultaneous use of wearables and connected mobile apps. Wrist-worn commercial consumer devices such as wristbands were the most prevalent, accounting for 66% (45/68) of the wearables identified in our review. Approximately half of the data from the medical domain (32/68, 47%) focused on studies involving participants with chronic illnesses or disorders. Overall, 29 usability attributes were identified, and 5 attributes were frequently used for evaluation: satisfaction (34/68, 50%), ease of use (27/68, 40%), user experience (16/68, 24%), perceived usefulness (18/68, 26%), and effectiveness (15/68, 22%). Only 10% (7/68) of the studies used a user- or human-centered design paradigm for usability evaluation. CONCLUSIONS Our scoping review identified the types and categories of wearable devices and mHealth apps, their frequency of use in studies, and their implementation in the medical context. In addition, we examined the usability evaluation of these technologies: methods, attributes, and frameworks. Within the array of available wearables and mHealth apps, health care providers encounter the challenge of selecting devices and companion apps that are effective, user-friendly, and compatible with user interactions. The current gap in usability and user experience in health care research limits our understanding of the strengths and limitations of wearable technologies and their companion apps. Additional research is necessary to overcome these limitations.

Visualizing urban data has different purposes. Besides more traditional goals such as supporting experts to decide on smart city policies, supporting citizens to understand aspects of the city relevant to one’s everyday life needs different visualization approaches. In contrast to urban dashboards, which typically show various data sources in a more or less unified way, visualizations tailored for one specific task may be more appropriate for citizens. This paper introduces data experience points where people can experience data on location on their own device, and explore and understand urban phenomena through visualizations. Based on an expert workshop, we propose a set of design goals for these data experience points, and demonstrate the concept through a case study of visualizing air quality data. We designed and implemented multiple prototypes in this case study, and gathered feedback at a public outreach event.

In this proposed panel, we will discuss the practice of Making with Data—the practice of creating physical artifacts that represent a dataset. This topic lies at the intersection of several CHI communities: data visualization, fabrication, and tangible interaction. Our goal is to discuss contemporary practices, but also to envision future ways that we might continue to make physical representations of data in the future, given emerging fabrication techniques, data representation practices, and desired interactions and experiences with data.

Background: Visual analysis and data delivery in the form of visualizations are of great importance in health care, as such forms of presentation can reduce errors and improve care and can also help provide new insights into long-term disease progression. Information visualization and visual analytics also address the complexity of long-term, time-oriented patient data by reducing inherent complexity and facilitating a focus on underlying and hidden patterns. Objective: This review aims to provide an overview of visualization techniques for time-oriented data in health care, supporting the comparison of patients. We systematically collected literature and report on the visualization techniques supporting the comparison of time-based data sets of single patients with those of multiple patients or their cohorts and summarized the use of these techniques. Methods: This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. After all collected articles were screened by 16 reviewers according to the criteria, 6 reviewers extracted the set of variables under investigation. The characteristics of these variables were based on existing taxonomies or identified through open coding. Results: Of the 249 screened articles, we identified 22 (8.8%) that fit all criteria and reviewed them in depth. We collected and synthesized findings from these articles for medical aspects such as medical context, medical objective, and medical data type, as well as for the core investigated aspects of visualization techniques, interaction techniques, and supported tasks. The extracted articles were published between 2003 and 2019 and were mostly situated in clinical research. These systems used a wide range of visualization techniques, most frequently showing changes over time. Timelines and temporal line charts occurred 8 times each, followed by histograms with 7 occurrences and scatterplots with 5 occurrences. We report on the findings quantitatively through visual summarization, as well as qualitatively. Conclusions: The articles under review in general mitigated complexity through visualization and supported diverse medical objectives. We identified 3 distinct patient entities: single patients, multiple patients, and cohorts. Cohorts were typically visualized in condensed form, either through prior data aggregation or through visual summarization, whereas visualization of individual patients often contained finer details. All the systems provided mechanisms for viewing and comparing patient data. However, explicitly comparing a single patient with multiple patients or a cohort was supported only by a few systems. These systems mainly use basic visualization techniques, with some using novel visualizations tailored to a specific task. Overall, we found the visual comparison of measurements between single and multiple patients or cohorts to be underdeveloped, and we argue for further research in a systematic review, as well as the usefulness of a design space.

BACKGROUND The visual analysis and delivery of data in the form of visualizations is of great importance in healthcare, as such forms of presentation can reduce errors and improve care, and can also help provide new insights into long-term disease progression. Information visualization and visual analytics also address the complexity of long-term, time-oriented patient data by reducing inherent complexity and facilitating focus on underlying and hidden patterns. OBJECTIVE Aim of this review is to give an overview of visualization techniques of time-oriented data in health care supporting the comparison of patients. We systematically collect literature and report on visualization techniques supporting the task of comparing time-based datasets of single patients with those of multiple patients or their cohorts, and summarize the usage of these techniques. Visualization techniques are grouped according to the medical characteristics and other relevant visualization aspects like data types, interactions and tasks. METHODS This scoping review used the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. After all collected articles were screened by 16 reviewers according to the criteria, 6 reviewers extracted the set of variables under investigation. The characteristics of these variables were based on existing taxonomies or identified through open coding. RESULTS Out of 249 screened articles, we identified 22 fitting all criteria, and reviewed these in-depth. We collected and synthesized findings from these articles for medical aspects such as medical context, medical objective, and medical data type, as well as for the core investigated aspects of visualization technique, interaction technique, and supported tasks. The extracted articles were published between 2003 and 2019, and mostly situated in clinical research. The systems use a wide range of visualization techniques, most frequently showing some change over time. Timelines and temporal line charts occur eight times each, followed by histograms with seven occurrences and scatterplots with five. We report on the findings quantitatively through visual summarization, and qualitatively. CONCLUSIONS The articles under review in general mitigate complexity through visualization and support diverse medical objectives. We identified three distinct patient entities: single patients, multiple patients, and cohorts. Cohorts typically are visualized in condensed form either through prior data aggregation or through visual summarization, whereas visualization of individual patients often contains finer details. All systems provide mechanisms to view and compare patient data. Explicitly comparing a single patient to multiple patients or a cohort, however, is supported only by a few systems. These systems mainly use basic visualization techniques with some employing novel visualizations tailored for a specific task. Overall, we found the visual comparison of measurements between single and multiple patients or cohorts to be underdeveloped, and argue for further research in a systematic review, and the usefulness of a design space.

Since the digitalization of urban mobility, such systems generate large and heterogenous data sets. Handling these, however, is still a major challenge. To help people making sense of urban data, skills in data literacy are needed. In this paper, we present results and insights from a set of mobility visualization projects, students from computer science and design developed over one semester. The resulting prototypes visualize (a) user-generated bike trajectories, (b) population movement, and (c) public transit passengers. After a brief justification on why we find urban mobility a practical domain for teaching data literacy, we introduce the course and describe its set and setting. For each project, we report on the challenge, the data, the visualization prototype, and the impact these projects had. Our contribution is twofold: in the description of the problem-oriented course and its results, and in the reflection of our approach and our lessons learnt.