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

Jibing Gong, Li Cui, Kejiang Xiao and Rui Wang

International Journal of Distributed Sensor Networks, 2012, vol. 8, issue 12, 602358

Abstract: 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.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:8:y:2012:i:12:p:602358

DOI: 10.1155/2012/602358

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