Predicting Nocturnal Hypoglycemia Using a Non-Parametric Insulin Action Model

被引:1
|
作者
Stahl, Fredrik [1 ]
Johansson, Rolf [1 ]
Olsson, Mona Landin [2 ]
机构
[1] Lund Univ, Dept Automat Control, Lund, Sweden
[2] Lund Univ, Dept Endocrinol, Lund, Sweden
来源
2015 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC 2015): BIG DATA ANALYTICS FOR HUMAN-CENTRIC SYSTEMS | 2015年
关键词
Diabetes; non-parametric model; prediction; GLUCOSE; TYPE-1;
D O I
10.1109/SMC.2015.280
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Nocturnal hypoglycemia is a common and potentially very dangerous condition facing persons with insulin-treated diabetes. To reduce the risk of going low while sleeping, many patient wilfully elevate their glucose level before bedtime, thereby also eroding the conditions for a sound glucose control for the next day. Recent advances in sensor technology allow for real-time frequent monitoring of the glucose level, and the road map towards an artificial pancreas involves combining an insulin pump with such sensors. The first steps towards a more autonomous insulin pump have been taken by allowing the pump to suspend the insulin supply when a hypoglycemic episode is imminent. This feature relies on algorithms for predicting the nocturnal event. In this paper, we present a novel model for this purpose. In comparison to previous methods, a better trade-off between sensitivity and false alarm rate was achieved, as well as improved warning time.
引用
收藏
页码:1583 / 1588
页数:6
相关论文
共 50 条
  • [1] Using Non-parametric Count Model for Credit Scoring
    Sami Mestiri
    Abdeljelil Farhat
    Journal of Quantitative Economics, 2021, 19 : 39 - 49
  • [2] Using Non-parametric Count Model for Credit Scoring
    Mestiri, Sami
    Farhat, Abdeljelil
    JOURNAL OF QUANTITATIVE ECONOMICS, 2021, 19 (01) : 39 - 49
  • [3] SOMPNN: an efficient non-parametric model for predicting transmembrane helices
    Yu, Dong-Jun
    Shen, Hong-Bin
    Yang, Jing-Yu
    AMINO ACIDS, 2012, 42 (06) : 2195 - 2205
  • [4] SOMPNN: an efficient non-parametric model for predicting transmembrane helices
    Dong-Jun Yu
    Hong-Bin Shen
    Jing-Yu Yang
    Amino Acids, 2012, 42 : 2195 - 2205
  • [5] AN EFFICIENT VIDEO CODING TECHNIQUE USING A NOVEL NON-PARAMETRIC BACKGROUND MODEL
    Chakraborty, Subrata
    Paul, Manoranjan
    Murshed, Manzur
    Ali, Mortuza
    2014 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO WORKSHOPS (ICMEW), 2014,
  • [6] Non-parametric estimation of a multiscale CHARN model using SVR
    Safari, Amir
    Seese, Detlef
    QUANTITATIVE FINANCE, 2009, 9 (01) : 105 - 121
  • [7] A comparison and prediction of total fertility rate using parametric, non-parametric, and Bayesian model
    Oh, Jinho
    KOREAN JOURNAL OF APPLIED STATISTICS, 2018, 31 (06) : 677 - 692
  • [8] A non-parametric hysteresis model for magnetorheological dampers
    Mohammadi, Ardeshir Karami
    Sheibani, Mohammad
    JOURNAL OF VIBROENGINEERING, 2011, 13 (03) : 451 - 460
  • [9] Predicting fertility from seminal traits: Performance of several parametric and non-parametric procedures
    Piles, M.
    Diez, J.
    del Coz, J. J.
    Montanes, E.
    Quevedo, J. R.
    Ramon, J.
    Rafel, O.
    Lopez-Bejar, M.
    Tusell, L.
    LIVESTOCK SCIENCE, 2013, 155 (01) : 137 - 147
  • [10] Adaptive weighted non-parametric background model for efficient video coding
    Chakraborty, Subrata
    Paul, Manoranjan
    Murshed, Manzur
    Ali, Mortuza
    NEUROCOMPUTING, 2017, 226 : 35 - 45