| Name: | Description: | Size: | Format: | |
|---|---|---|---|---|
| 238.41 KB | Adobe PDF |
Advisor(s)
Abstract(s)
Smartphones are everywhere, and they are a very
attractive platform to perform unobtrusive monitoring of users.
In this work, we use common features of modern smartphones
to build a human activity recognition (HAR) system for elderly
care. We have built a classifier that detects the transport mode
of the user including whether an individual is inactive, walking,
in bus, in car, in train or in metro. We evaluated our approach
using over 24 hours of transportation data from a group of 15
individuals. Our tests show that our classifier can detect the
transportation mode with over 90% accuracy.
Description
Keywords
Inertial Sensors Accelerometer Classification Algorithms Transport Detection Smartphones
Citation
Publisher
Institute of Electrical and Electronics Engineers