dc.contributor.author | Duce, David A. | en_US |
dc.contributor.author | Martin, Clare | en_US |
dc.contributor.author | Russell, Alex | en_US |
dc.contributor.author | Brown, Dan | en_US |
dc.contributor.author | Aldea, Arantza | en_US |
dc.contributor.author | Alshaigy, Bedour | en_US |
dc.contributor.author | Harrison, Rachel | en_US |
dc.contributor.author | Waite, Marion | en_US |
dc.contributor.author | Leal, Yenny | en_US |
dc.contributor.author | Wos, Marzena | en_US |
dc.contributor.author | Fernandez-Balsells, Mercè | en_US |
dc.contributor.author | Real, José Manuel Fernández | en_US |
dc.contributor.author | Nita, Lucian | en_US |
dc.contributor.author | López, Beatriz | en_US |
dc.contributor.author | Massana, Joaquim | en_US |
dc.contributor.author | Avari, Parizad | en_US |
dc.contributor.author | Herrero, Pau | en_US |
dc.contributor.author | Jugnee, Narvada | en_US |
dc.contributor.author | Oliver, Nick | en_US |
dc.contributor.author | Reddy, Monika | en_US |
dc.contributor.editor | Ritsos, Panagiotis D. and Xu, Kai | en_US |
dc.date.accessioned | 2020-09-10T06:27:40Z | |
dc.date.available | 2020-09-10T06:27:40Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-3-03868-122-9 | |
dc.identifier.uri | https://doi.org/10.2312/cgvc.20201144 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/cgvc20201144 | |
dc.description.abstract | This article explores the role for visualization in interpreting data collected by a customised analytics framework within a healthcare technology project. It draws on the work of the EU-funded PEPPER project, which has created a personalised decision-support system for people with type 1 diabetes. Our approach was an exercise in exploratory visualization, as described by Bergeron's three category taxonomy. The charts revealed different patterns of interaction, including variability in insulin dosing schedule, and potential causes of rejected advice. These insights into user behaviour are of especial value to this field, as they may help clinicians and developers understand some of the obstacles that hinder the uptake of diabetes technology. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | Human centered computing | |
dc.subject | Information visualization | |
dc.subject | Applied computing | |
dc.subject | Health informatics | |
dc.title | Visualizing Usage Data from a Diabetes Management System | en_US |
dc.description.seriesinformation | Computer Graphics and Visual Computing (CGVC) | |
dc.description.sectionheaders | Visualisation and Machine Learning | |
dc.identifier.doi | 10.2312/cgvc.20201144 | |
dc.identifier.pages | 1-9 | |