Research Article
Identifying and Visualizing Relevant Deviations in Longitudinal Sensor Patterns for Care Professionals
@INPROCEEDINGS{10.4108/icst.pervasivehealth.2013.252130, author={Saskia Robben and Mario Boot and Marije Kanis and Ben Krose}, title={Identifying and Visualizing Relevant Deviations in Longitudinal Sensor Patterns for Care Professionals}, proceedings={1st International Workshop on Lifelogging for Pervasive Health}, publisher={IEEE}, proceedings_a={LIFELOGGING}, year={2013}, month={5}, keywords={visualization ambient monitoring activity monitoring adl sensor network}, doi={10.4108/icst.pervasivehealth.2013.252130} }- Saskia Robben
Mario Boot
Marije Kanis
Ben Krose
Year: 2013
Identifying and Visualizing Relevant Deviations in Longitudinal Sensor Patterns for Care Professionals
LIFELOGGING
IEEE
DOI: 10.4108/icst.pervasivehealth.2013.252130
Abstract
Sensor technology is increasingly applied for the purpose of monitoring elderly's Activities of Daily Living (ADL), a set of activities used by physicians to benchmark physical and cognitive decline. Visualizing deviations in ADL can help medical specialists and nurses to recognize disease symptoms at an early stage. This paper presents possible visualizations for identifying such deviations. These visualizations have been iteratively explored and developed with three different medical specialists to better understand which deviations are relevant according to the different medical specialisms and explore how these deviations could be best presented. The study results suggest that the participants found a monthly bar graph in which activities are represented by colours as the most suitable from the ones presented. Although the visualisations of every ADL was found to be more or less relevant by the different medical specialists, the preference for focusing on specific ADL's varied from specialist to specialist.
