DocumentCode
2314803
Title
Multivariate statistical analysis methods to investigate interindividual glucose dynamics for subjects with type 1 diabetes mellitus
Author
Zhao, Chunhui ; Sun, Youxian ; Gao, Furong
Author_Institution
Dept. of Control Sci. & Eng., Zhejiang Univ., Hangzhou, China
fYear
2012
fDate
6-8 July 2012
Firstpage
4989
Lastpage
4994
Abstract
This paper investigates the interindividual variability of underlying glucose dynamics using multivariate statistical analysis methods for subjects with type 1 diabetes mellitus. Here two types of glucose dynamics are defined, the general dynamics and the output-relevant predictive dynamics. The concerned important issues are whether the underlying glucose dynamics change from subject to subject? Can a global (or universal) empirical model be developed from glucose data for a single subject and then used to explain the glucose dynamics for other subjects? These and related issues are investigated using multivariate statistical analysis methods based on clinical data for two groups of subjects. Together, these findings provide insights into more efficient development of data-driven models to understand and capture the glucose information in diabetes subjects.
Keywords
blood; diseases; medical control systems; patient monitoring; statistical analysis; data-driven models; global empirical model; interindividual glucose dynamics; multivariate statistical analysis methods; output-relevant predictive dynamics; type 1 diabetes mellitus; universal empirical model; Analytical models; Data models; Diabetes; Predictive models; Principal component analysis; Sugar; Continuous glucose monitor (CGM); Diabetes; Glucose dynamics; Glucose prediction; Interindividual variability;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location
Beijing
Print_ISBN
978-1-4673-1397-1
Type
conf
DOI
10.1109/WCICA.2012.6359424
Filename
6359424
Link To Document