Predicting human subcutaneous glucose concentration in real time: A universal data-driven approach

Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS

Volumn , Issue , 2011, Pages 7945-7948

  Lu, Yinghui ^a   Rajaraman, Srinivasan ^a   Ward, W Kenneth ^b   Vigersky, Robert A ^c   Reifman, Jaques ^d  

^a U S ARMY MEDICAL RESEARCH AND MATERIEL COMMAND   (United States)

^b OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

^c WALTER REED ARMY MEDICAL CENTER   (United States)

^d TATRC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTO REGRESSIVE MODELS; CONTINUOUS GLUCOSE MONITORING; DATA-DRIVEN; DATA-DRIVEN ALGORITHM; DATA-DRIVEN APPROACH; DIABETIC PATIENT; GLUCOSE CONCENTRATION; GLUCOSE LEVEL; MODEL-BASED OPC; OFFLINE; PREDICTION MODEL; REAL TIME; REAL TIME FILTERING; REAL-TIME IMPLEMENTATIONS; SHORT TERM PREDICTION;

FORECASTING; MATHEMATICAL MODELS; REAL TIME CONTROL;

GLUCOSE;

GLUCOSE;

ADOLESCENT; ADULT; AGED; ALGORITHM; ARTICLE; BIOLOGICAL MODEL; BLOOD GLUCOSE MONITORING; COMPUTER SIMULATION; HUMAN; METABOLISM; METHODOLOGY; MIDDLE AGED; REGRESSION ANALYSIS; SUBCUTANEOUS TISSUE; TIME; YOUNG ADULT;

ADOLESCENT; ADULT; AGED; ALGORITHMS; BLOOD GLUCOSE SELF-MONITORING; COMPUTER SIMULATION; GLUCOSE; HUMANS; MIDDLE AGED; MODELS, BIOLOGICAL; REGRESSION ANALYSIS; SUBCUTANEOUS TISSUE; TIME FACTORS; YOUNG ADULT;

EID: 84861658913     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IEMBS.2011.6091959     Document Type: Conference Paper

References (8)

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