論文アブストラクト： The position and workings of interactive interior elements matter greatly on the relations people may enact. This paper reports on the conception and evaluation of an interactive table and its interior effects designed to support sensitive consultations between healthcare personnel, patients and relatives as they happen during treatment of cancer diseases in a hospital department of oncology. The interior design includes the physical shape of artefact, its digital functionality and how the seating around it is to take place. The design of the table is substantiated through observations of current practice, framing of the design challenge, conceptualization, and exploring form giving alternatives. Through a set of evaluations in actual use settings it is argued how the design concept of the table as interactive interior points to how notions in interaction proxemics should be rearticulated. In particular, this paper argues how proxemics thresholds should be regarded as dynamic and relational.
論文アブストラクト： Clinical practice is heavily reliant on the use of unstructured text to document patient stories due to its expressive and flexible nature. However, a physician's capacity to recover information from text for clinical overview is severely affected when records get longer and time pressure increases. Data visualization strategies have been explored to aid in information retrieval by replacing text with graphical summaries, though often at the cost of omitting important text features. This causes physician mistrust and limits real-world adoption. This work presents our investigation into the role and use of text in clinical practice, and reports on efforts to assess the best of both worlds---text and visualization---to facilitate clinical overview. We report on insights garnered from a field study, and the lessons learned from an iterative design process and evaluation of a text-visualization prototype, MedStory, with 14 medical professionals. The results led to a number of grounded design recommendations to guide visualization design to support clinical text overview.
論文アブストラクト： Type 2 Diabetes Mellitus (T2DM) is a common chronic condition that requires management of one's lifestyle, including nutrition. Critically, patients often lack a clear understanding of how everyday meals impact their blood glucose. New predictive analytics approaches can provide personalized mealtime blood glucose forecasts. While communicating forecasts can be challenging, effective strategies for doing so remain little explored. In this study, we conducted focus groups with 13 participants to identify approaches to visualizing personalized blood glucose forecasts that can promote diabetes self-management and understand key styles and visual features that resonate with individuals with diabetes. Focus groups demonstrated that individuals rely on simple heuristics and tend to take a reactive approach to their health and nutrition management. Further, the study highlighted the need for simple and explicit, yet information-rich design. Effective visualizations were found to utilize common metaphors alongside words, numbers, and colors to convey a sense of authority and encourage action and learning.
論文アブストラクト： The Electrocardiogram (ECG) is commonly used to detect arrhythmias. Traditionally, a single ECG observation is used for diagnosis, making it difficult to detect irregular arrhythmias. Recent technology developments, however, have made it cost-effective to collect large amounts of raw ECG data over time. This promises to improve diagnosis accuracy, but the large data volume presents new challenges for cardiologists. This paper introduces ECGLens, an interactive system for arrhythmia detection and analysis using large-scale ECG data. Our system integrates an automatic heartbeat classification algorithm based on convolutional neural network, an outlier detection algorithm, and a set of rich interaction techniques. We also introduce A-glyph, a novel glyph designed to improve the readability and comparison of ECG signals. We report results from a comprehensive user study showing that A-glyph improves the efficiency in arrhythmia detection, and demonstrate the effectiveness of ECGLens in arrhythmia detection through two expert interviews.