Title :
Asthmatic attacks prediction considering weather factors based on Fuzzy-AR model
Author :
Kaku, Yusho ; Kuramoto, Kei ; Kobashi, Syoji ; Hata, Yutaka
Author_Institution :
Grad. Sch. of Eng., Univ. of Hyogo, Kamigori, Japan
Abstract :
Asthma causes the bronchus inflammation, and makes breathing impossible. In worst case, asthma leads to death due to dyspnea. If we can predict that children cause asthmatic attacks, they can prevent from asthmatic attacks with minimum attention. Therefore, asthmatic attacks prediction system is desired. As a prediction system using time series data, there is Fuzzy-AR model that can consider multi factors. In this paper, we propose a prediction method of the number of asthmatic attacks on next month based on Fuzzy-AR model. The proposed method considers weather factors; temperature, atmospheric pressure and humidity data. This method is applied to asthmatic attacks data from Himeji city Medical Association. As a comparison method, AR model is applied to same data. The experimental results shown that the proposed method predicts the number of asthmatic attacks better than AR model.
Keywords :
autoregressive processes; health care; medical computing; time series; Himeji city Medical Association; asthmatic attacks data; asthmatic attacks prediction; atmospheric pressure; bronchus inflammation; dyspnea; fuzzy-AR model; humidity data; prediction method; prediction system; time series data; weather factors; Atmospheric modeling; Brain modeling; Correlation; Data models; Humidity; Predictive models; asthmatic attacks; autoregressive model; healthcare sistem; prediction model; time-series data;
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2012 IEEE International Conference on
Conference_Location :
Brisbane, QLD
Print_ISBN :
978-1-4673-1507-4
Electronic_ISBN :
1098-7584
DOI :
10.1109/FUZZ-IEEE.2012.6251346