TY - GEN
T1 - A mobile data analysis framework for environmental health decision support
AU - Bae, Wan D.
AU - Alkobaisi, Shayma
AU - Narayanappa, Sada
AU - Liu, Cheng C.
PY - 2012
Y1 - 2012
N2 - Relations between negative health effects like asthma and lung cancer and elevated levels of the environmental factors, such as air pollution, tobacco smoke and humidity, have been detected in several large scale exposure studies. Thus, public health care and service systems require the ability to track, monitor, store, and analyze individual moving trajectories along with several environmental conditions the individual is exposed to in order to identify meaningful relationships among theses data and derive conclusions for environmental health decision support. With continued advances in information technology, patients can be monitored with numerous intelligent devices. Sensors can be integrated into their mobile devices such as smart phones for continuous health assistance and disease attack prevention. However, researchers must overcome many challenges, such as data acquisition, data scales and data uncertainty, in order to develop a real-time health monitoring system. In this paper, we propose a system framework for modeling and analyzing individual exposure to environmental triggers of asthma attacks. The proposed system can provide a tool to develop more accurate asthma prevention and care plans enabled by real-time patient monitoring and communication through alerts for potential environmental triggers.
AB - Relations between negative health effects like asthma and lung cancer and elevated levels of the environmental factors, such as air pollution, tobacco smoke and humidity, have been detected in several large scale exposure studies. Thus, public health care and service systems require the ability to track, monitor, store, and analyze individual moving trajectories along with several environmental conditions the individual is exposed to in order to identify meaningful relationships among theses data and derive conclusions for environmental health decision support. With continued advances in information technology, patients can be monitored with numerous intelligent devices. Sensors can be integrated into their mobile devices such as smart phones for continuous health assistance and disease attack prevention. However, researchers must overcome many challenges, such as data acquisition, data scales and data uncertainty, in order to develop a real-time health monitoring system. In this paper, we propose a system framework for modeling and analyzing individual exposure to environmental triggers of asthma attacks. The proposed system can provide a tool to develop more accurate asthma prevention and care plans enabled by real-time patient monitoring and communication through alerts for potential environmental triggers.
KW - asthma
KW - environmental factors
KW - health monitoring
KW - public health
KW - uncertain trajectories
UR - http://www.scopus.com/inward/record.url?scp=84863963781&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863963781&partnerID=8YFLogxK
U2 - 10.1109/ITNG.2012.31
DO - 10.1109/ITNG.2012.31
M3 - Conference contribution
AN - SCOPUS:84863963781
SN - 9780769546544
T3 - Proceedings of the 9th International Conference on Information Technology, ITNG 2012
SP - 155
EP - 161
BT - Proceedings of the 9th International Conference on Information Technology, ITNG 2012
T2 - 9th International Conference on Information Technology, ITNG 2012
Y2 - 16 April 2012 through 18 April 2012
ER -