Name
Abstract | ||
|---|---|---|
Context-aware sensing is an integral part of the Body Sensor Network (BSN) design and it allows the understanding of intrinsic characteristics of the sensed signal and determination of how BSNs should react to different events and adapt its monitoring behaviour. The purpose of this paper is to propose a novel spatiotemporal self-organising map that minimises the number of neurons involved whilst maintaining a high accuracy in class separation for both static and dynamic activities. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/BSN.2006.5 | BSN |
Keywords | Field | DocType |
dynamic activity,body sensor network,monitoring behaviour,intrinsic characteristic,spatio-temporal architecture,novel spatiotemporal,context aware sensing,class separation,different event,integral part,high accuracy,artificial neural networks,ubiquitous computing,pervasive computing,computer architecture,patient monitoring,wireless sensor networks,acceleration | Data mining,Computer science,Remote patient monitoring,Real-time computing,Artificial intelligence,Ubiquitous computing,Artificial neural network,Computer vision,Architecture,Biomedical equipment,Context awareness,Wireless sensor network,Self organising maps | Conference |
ISBN | Citations | PageRank |
0-7695-2547-4 | 3 | 0.50 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Surapa Thiemjarus | 1 | 192 | 15.64 |
| Benny Lo | 2 | 403 | 37.89 |
| Guang-Zhong Yang | 3 | 2812 | 297.66 |