NDLI: Wearable Sensor-Based Behavioral Anomaly Detection in Smart Assisted Living Systems

Content Provider	IEEE Xplore Digital Library
Author	Chun Zhu Weihua Sheng Meiqin Liu
Copyright Year	2004
Abstract	Detecting behavioral anomalies in human daily life is important to developing smart assisted-living systems for elderly care. Based on data collected from wearable motion sensors and the associated locational context, this paper presents a coherent anomaly detection framework to effectively detect different behavioral anomalies in human daily life. Four types of anomalies, including spatial anomaly, timing anomaly, duration anomaly, and sequence anomaly, are detected using a probabilistic theoretical framework. This framework is based on complex activity recognition using dynamic Bayesian network modeling. The maximum-likelihood estimation algorithm and Laplace smoothing are used in learning the parameters in the anomaly detection model. We conducted experimental evaluation in a mock apartment environment, and the results verified the effectiveness of the proposed framework. We expect that this behavioral anomaly detection system can be integrated into future smart homes for elderly care.
Sponsorship	IEEE Robotics and Automation Society
Starting Page	1225
Ending Page	1234
Page Count	10
File Size	1304072
File Format	PDF
ISSN	15455955
Volume Number	12
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent sensors Robot sensing systems Smart homes Assisted living Wearable sensors wearable computing Anomaly detection assisted living smart home
Content Type	Text
Resource Type	Article
Subject	Control and Systems Engineering Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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