MPD-Model : A Distributed Multipreference-Driven Data Fusion Model and Its Application in a WSNs-Based Healthcare Monitoring System

We first propose an MPD-Model, a novel distributed multipreference-driven data fusion model for WSNs. Here, preferences are looked as the core elements of collaboration mechanism in a data fusion procedure. We then present MFA, a distributed multi-preference feature-level fusion algorithm based on w...

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Bibliographic Details
Published in:International journal of distributed sensor networks 2012-01, Vol.2012 (2012), p.1-13
Main Authors: Gong, Jibing, Cui, Li, Xiao, Kejiang, Wang, Rui
Format: Article
Language:English
Subjects:
Accuracy
Armed forces
Classification
Data processing
Environmental monitoring
Intelligence
Methods
Preferences
Science
Sensors
Studies
Wireless networks
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Summary:We first propose an MPD-Model, a novel distributed multipreference-driven data fusion model for WSNs. Here, preferences are looked as the core elements of collaboration mechanism in a data fusion procedure. We then present MFA, a distributed multi-preference feature-level fusion algorithm based on weighted average method. Next, to implement feature extraction of wrist-pulse data, we propose FEA, a light-weight adaptive feature extraction algorithm for time series sensed data. Simultaneously, we design TFD-Pattern that is a unique human pulse pattern. Based on historical data, we propose an SVM-based algorithm for health status detection tasks. Finally, we implement the proposed methods in a real wearable healthcare monitoring system which had been previously developed in-house. We validate the proposed methods using real-world data sets with 2046 pulse samples. Experimental results show that the proposed methods outperform the baseline methods, and the proposed MPD-Model is reasonable and effective.
ISSN:1550-1329
1550-1477
1550-1477
DOI:10.1155/2012/602358