Abstract
In earlier studies, we have developed activity
recognition algorithm which are based on features
calculated
from 3D accelerometer sensor data placed on a hip, close
to
the centre of mass. In the development subjects have been
young adults. Now we study are the input features of the
algorithm generalized for older adults and for different
sensor
placement; in this case worn as a necklace. From the 3D
accelerometer resultant magnitude the following features
were
calculated for each second: spectral entropy, peak
frequency,
power and range. The frequency domain features behaved in
a
relatively stable manner in the set-ups but the time
domain
features differed significantly from statistical and
algorithm
perspective between the set-ups. By developing time
domain
features to be more inter-individual independent would be
beneficial for activity recognition algorithms
| Original language | English |
|---|---|
| Title of host publication | Proceedings |
| Subtitle of host publication | Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 |
| Publisher | IEEE Institute of Electrical and Electronic Engineers |
| Pages | 7885-7887 |
| ISBN (Electronic) | 978-1-4244-4122-8 |
| ISBN (Print) | 978-1-4244-4121-1 |
| DOIs | |
| Publication status | Published - 2011 |
| MoE publication type | A4 Article in a conference publication |
| Event | 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society: EMBC 2011 - Boston, United States Duration: 30 Aug 2011 → 3 Sept 2011 |
Conference
| Conference | 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society |
|---|---|
| Country/Territory | United States |
| City | Boston |
| Period | 30/08/11 → 3/09/11 |
Keywords
- Accelerometer
- context recognition
- older people