Please use this identifier to cite or link to this item:
|Title:||Detection of activities by wireless sensors for daily life surveillance: Eating and drinking|
|Authors:||Zhang, S. |
Ang Jr., M.H.
|Keywords:||Eating and drinking|
|Citation:||Zhang, S., Ang Jr., M.H., Xiao, W., Tham, C.K. (2009-03). Detection of activities by wireless sensors for daily life surveillance: Eating and drinking. Sensors 9 (3) : 1499-1517. ScholarBank@NUS Repository. https://doi.org/10.3390/s90301499|
|Abstract:||This paper introduces a two-stage approach to the detection of people eating and/or drinking for the purposes of surveillance of daily life. With the sole use of wearable accelerometer sensor attached to somebody's (man or a woman) wrists, this two-stage approach consists of feature extraction followed by classification. At the first stage, based on the limb's three dimensional kinematics movement model and the Extended Kalman Filter (EKF), the realtime arm movement features described by Euler angles are extracted from the raw accelerometer measurement data. In the latter stage, the Hierarchical Temporal Memory (HTM) network is adopted to classify the extracted features of the eating/drinking activities based on the space and time varying property of the features, by making use of the powerful modelling capability of HTM network on dynamic signals which is varying with both space and time. The proposed approach is tested through the real eating and drinking activities using the three dimensional accelerometers. Experimental results show that the EKF and HTM based two-stage approach can perform the activity detection successfully with very high accuracy. © 2009 by the authors; licensee Molecular Diversity Preservation International, Basel, Switzerland.|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Jun 15, 2018
WEB OF SCIENCETM
checked on May 15, 2018
checked on Jun 8, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.