Name
Abstract | ||
|---|---|---|
Physiological monitoring has been used in a wide range of scenarios to assist in disease diagnosis, athlete monitoring and other activities. There are also many opportunities in analysing aggregate data from groups of people rather than individuals such as public event monitoring or athletic team performance optimisation. Numerous difficulties exist pertaining to this, particularly concerning how to process and transform the resulting physiological data in real-time when many devices are producing data. This paper proposes a system that is designed to monitor, analyse and report physiological data in real-time by leveraging mobile devices as distributed processors. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/PIMRC.2012.6362782 | PIMRC |
Keywords | Field | DocType |
biomedical telemetry,diseases,mobile handsets,athlete monitoring,athletic team performance optimisation,disease diagnosis,distributed processors,distributed real-time physiological processing,mobile devices,mobile environments,physiological data,public event monitoring | Event monitoring,Decision tree,Base station,Wireless,Computer science,Physiological monitoring,Computer network,Peer to peer computing,Real-time computing,Mobile device,Aggregate data | Conference |
Citations | PageRank | References |
0 | 0.34 | 27 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| James Meneghello | 1 | 7 | 1.51 |
| Kevin Lee | 2 | 340 | 27.53 |
| Kiel Gilleade | 3 | 49 | 4.19 |