Name
Abstract | ||
|---|---|---|
In our work we envision the use of context awareness to complement and improve telemedicine services. One concrete example is the recognition of physical activity (PA) for therapies and treatments. The usage of context can provide newer services by assisting medical professionals and patients to obtain implicit information. We introduce the Context Aware Remote Monitoring Assistant (CARMA), an application implemented on the MATRIX telemedicine middleware platform. It enables activity recognition for patients using non-obtrusive devices. In this paper, a movement recognition approach is investigated using a smartphone with a built-in accelerometer. Experiments were carried out to compare the influences of classification algorithms, features and combinations for feature extraction conditions on the recognition accuracy. The obtained results indicated that the approach is viable and shows much potential. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ISWCS.2010.5624490 | ISWCS |
Keywords | DocType | ISSN |
recognition accuracy,mobile handsets,carma,telemedicine,context aware remote monitoring assistant,patient monitoring,smartphone,feature extraction,context awareness,matrix telemedicine middleware platform,activity recognition,accelerometers,middleware,movement recognition,remote monitoring,classification algorithms,bagging,physical activity,accuracy | Conference | 2154-0217 |
ISBN | Citations | PageRank |
978-1-4244-6315-2 | 36 | 1.83 |
References | Authors | |
5 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sian Lun Lau | 1 | 81 | 11.48 |
| Immanuel König | 2 | 65 | 4.55 |
| Klaus David | 3 | 269 | 34.41 |
| Baback Parandian | 4 | 36 | 1.83 |
| Christine Carius-Düssel | 5 | 37 | 2.22 |
| Martin Schultz | 6 | 53 | 5.35 |