A framework for supervising lifestyle diseases using long-term activity monitoring.
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.
Department of Computer Engineering, Kyung Hee University, Seocheon-dong, Giheung-gu, Yongin-si, Gyeonggi-do, 446-701, Korea. ykhan@khu.ac.kr
Yongkoo
Y
Han
Manhyung
M
Han
Sungyoung
S
Lee
A M Jehad
AM
Sarkar
Young-Koo
YK
Lee
D000203:Activities of Daily Living; D004194:Disease; D015438:Health Behavior; D006801:Humans; D008019:Life Style; D008991:Monitoring, Physiologic / Q000379:methods*; D009043:Motor Activity