Name
Abstract | ||
|---|---|---|
This work deals with the elimination of sensitivity to sensor orientation in the task of human daily activity recognition using a single miniature inertial sensor. The proposed method detects time intervals of walking, automatically estimating the orientation in these intervals and transforming the observed signals to a “virtual” sensor orientation. Classification results show that excellent performance, in terms of both precision and recall (up to 100%), is achieved, for long-term recordings in real-life settings. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/MLSP.2012.6349789 | Machine Learning for Signal Processing |
Keywords | Field | DocType |
biomedical equipment,medical signal processing,object recognition,sensors,automatic orientation estimation,human daily activity recognition,long term human activity recognition,single miniature inertial sensor,time intervals,virtual sensor orientation,Activity recognition,orientation estimation,wearable sensors | Computer vision,Activity recognition,Computer science,Precision and recall,Biomedical equipment,Speech recognition,Artificial intelligence,Cognitive neuroscience of visual object recognition | Conference |
ISSN | ISBN | Citations |
1551-2541 E-ISBN : 978-1-4673-1025-3 | 978-1-4673-1025-3 | 1 |
PageRank | References | Authors |
0.38 | 13 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Blanca Florentino-Liaño | 1 | 7 | 0.98 |
| Niamh O'Mahony | 2 | 18 | 2.62 |
| Antonio Artés-Rodríguez | 3 | 206 | 34.76 |
| Florentino-Liano, B. | 4 | 1 | 0.38 |
| Artes-Rodriguez, A. | 5 | 10 | 2.42 |