Health Monitor Agent Based on Neural Networks for Ubiquitous Healthcare Environment*

Authors:
Michael Angelo Salvo;Romeo Mark Mateo;Jaewan Lee;Malrey Lee
Affiliations:
School of Electronic and Information Engineering, Kunsan National University, Kunsan, Chonbuk, South Korea 573-701;School of Electronic and Information Engineering, Kunsan National University, Kunsan, Chonbuk, South Korea 573-701;School of Electronic and Information Engineering, Kunsan National University, Kunsan, Chonbuk, South Korea 573-701;School of Electronics and Information Engineering, Chonbuk National University, Jeonju, Chonbuk, South Korea 561-756
Venue:
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
Year:
2009

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Abstract

Environments such as healthcare systems rely on wireless sensor networks as one of the trends being established in today's industry. Being one of the most researched topics today, ubiquitous healthcare is mostly concerned with providing fast and efficient service. This paper proposes the Health Monitor Agent (HMA) to monitor patients' conditions, provide early detection of serious cases, and take appropriate action in case of emergency. We present this agent to the Ubiquitous and Intelligent Framework. The proposed agent recognizes medical conditions based on symptom patterns from the biosensors in the ubiquitous healthcare environment. The HMA classifies the symptom patterns into the correct medical condition using the multilayer perceptron (MLP). Our proposed algorithm recorded the highest accuracy rate compared to the ZeroR, Simple Logistic, and J48 algorithms.