Open AccessThis article is
- freely available
Detection of Activities by Wireless Sensors for Daily Life Surveillance: Eating and Drinking
Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576
Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117576
Networking Protocols Department, Institute for Infocomm Research, 1 Fusionopolis Way, No. 21-01 Connexis, South Tower, Singapore 138632
* Authors to whom correspondence should be addressed.
Received: 12 January 2009; Accepted: 20 February 2009 / Published: 3 March 2009
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.
Keywords: Wireless Sensor; HTM; Feature Extraction; Eating and Drinking; Euler Angle
Article StatisticsClick here to load and display the download statistics.
Notes: Multiple requests from the same IP address are counted as one view.
Cite This Article
MDPI and ACS Style
Zhang, S.; Ang, M.H., Jr.; Xiao, W.; Tham, C.K. Detection of Activities by Wireless Sensors for Daily Life Surveillance: Eating and Drinking. Sensors 2009, 9, 1499-1517.
Zhang S, Ang MH, Jr, Xiao W, Tham CK. Detection of Activities by Wireless Sensors for Daily Life Surveillance: Eating and Drinking. Sensors. 2009; 9(3):1499-1517.
Zhang, Sen; Ang, Marcelo H., Jr.; Xiao, Wendong; Tham, Chen Khong. 2009. "Detection of Activities by Wireless Sensors for Daily Life Surveillance: Eating and Drinking." Sensors 9, no. 3: 1499-1517.