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Sensors 2012, 12(5), 5363-5379; doi:10.3390/s120505363

A Framework for Supervising Lifestyle Diseases Using Long-Term Activity Monitoring

Department of Computer Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, Korea
Deptartment of Digital Information Engineering, Hankuk University of Foreign Studies, 89 Wangsan-ri, Mohyeon-myeon, Cheoin-gu, 449-791, Korea
Author to whom correspondence should be addressed.
Received: 6 March 2012 / Revised: 10 April 2012 / Accepted: 11 April 2012 / Published: 26 April 2012
(This article belongs to the Special Issue Ubiquitous Sensing)
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Activity monitoring of a person for a long-term would be helpful for controlling lifestyle associated diseases. Such diseases are often linked with the way a person lives. An unhealthy and irregular standard of living influences the risk of such diseases in the later part of one’s life. The symptoms and the initial signs of these diseases are common to the people with irregular lifestyle. In this paper, we propose a novel healthcare framework to manage lifestyle diseases using long-term activity monitoring. The framework recognizes the user’s activities with the help of the sensed data in runtime and reports the irregular and unhealthy activity patterns to a doctor and a caregiver. The proposed framework is a hierarchical structure that consists of three modules: activity recognition, activity pattern generation and lifestyle disease prediction. We show that it is possible to assess the possibility of lifestyle diseases from the sensor data. We also show the viability of the proposed framework. View Full-Text
Keywords: sensor system; ubiquitous healthcare system; activity recognition; lifestyle disease; framework sensor system; ubiquitous healthcare system; activity recognition; lifestyle disease; framework

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Han, Y.; Han, M.; Lee, S.; Sarkar, A.M.J.; Lee, Y.-K. A Framework for Supervising Lifestyle Diseases Using Long-Term Activity Monitoring. Sensors 2012, 12, 5363-5379.

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