Name
Abstract | ||
|---|---|---|
Dementia care requires care home staff to constantly balance daily duties and ad hoc demands. Reflection on the resulting patterns could help carers to improve their care practices. In this paper we describe the evaluation of new low-power proximity sensors in a care home to track and measure these patterns. Carers and residents wear sensors which broadcast a unique ID within a limited range, listen for other sensors, and store all received IDs to measure the co-location of other sensors. Using the sensors, on average 44% of a carer's shift could be matched to a specific resident or a documentation task. When the results were visualized to carers after the shift, carers could recognize behavior from the raw data and started to discuss care practices. The added value was more important to carers than their privacy. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.4108/icst.pervasivehealth.2013.251943 | Pervasive Computing Technologies for Healthcare |
Keywords | Field | DocType |
raw data,limited range,new low-power proximity sensor,care home,care practice,dementia care,care home staff,added value,documentation task,daily duty,documentation,neurophysiology,sensors | Nursing,Proximity sensor,Computer science,Physical therapy,Raw data,Biomedical equipment,Added value,Patient care,Documentation,Dementia | Conference |
ISSN | ISBN | Citations |
2153-1633 | 978-1-936968-80-0 | 4 |
PageRank | References | Authors |
0.47 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lars Müller | 1 | 57 | 7.41 |
| Mark Sonnentag | 2 | 4 | 0.47 |
| Stephan Heuer | 3 | 14 | 3.32 |