Rapid model identification for online subcutaneous glucose concentration prediction for new subjects with type i diabetes

IEEE Transactions on Biomedical Engineering

Volumn 62, Issue 5, 2015, Pages 1333-1344

  Zhao, Chunhui ^a   Yu, Chengxia ^a  

^a STATE KEY LABORATORY OF INDUSTRIAL CONTROL TECHNOLOGY   (China)

Author keywords

Auto regressive models with exogenous inputs (ARX); glucose prediction; model migration; rapid model identification; type I diabetes

Indexed keywords

GLUCOSE; SOCIAL NETWORKING (ONLINE); TIME SERIES ANALYSIS;

AUTO REGRESSIVE MODELS; CONVENTIONAL MODELING; EXOGENOUS INPUT; GENERALIZATION ABILITY; MODEL IDENTIFICATION; MODEL MIGRATIONS; RAPID MODEL DEVELOPMENT; TYPE I DIABETES;

FORECASTING;

GLUCOSE; GLUCOSE BLOOD LEVEL;

ACCURACY; ARTICLE; GLUCOSE BLOOD LEVEL; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; MODEL; ONLINE ANALYSIS; PREDICTION; ADOLESCENT; ADULT; ANALYSIS; BLOOD; BLOOD GLUCOSE MONITORING; CHILD; COMPUTER SIMULATION; PROCEDURES; STATISTICAL MODEL;

ADOLESCENT; ADULT; BLOOD GLUCOSE; BLOOD GLUCOSE SELF-MONITORING; CHILD; COMPUTER SIMULATION; DIABETES MELLITUS, TYPE 1; HUMANS; MODELS, STATISTICAL;

EID: 84929075114     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2014.2387293     Document Type: Article

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