Deep learning framework for detection of hypoglycemic episodes in children with type 1 diabetes

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

Volumn 2016-October, Issue , 2016, Pages 3503-3506

  San, Phyo Phyo ^a   Ling, Sai Ho ^b   Nguyen, Hung T ^b  

^a INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

^b UNIVERSITY OF TECHNOLOGY SYDNEY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

GLUCOSE BLOOD LEVEL;

ALGORITHM; ANALYSIS; ARTIFICIAL NEURAL NETWORK; BLOOD; CHILD; COMPLICATION; ELECTROCARDIOGRAPHY; GLUCOSE BLOOD LEVEL; HEART RATE; HUMAN; HYPOGLYCEMIA; INSULIN DEPENDENT DIABETES MELLITUS; PATHOPHYSIOLOGY; PHYSIOLOGY; PROCEDURES; SIGNAL PROCESSING;

ALGORITHMS; BLOOD GLUCOSE; CHILD; DIABETES MELLITUS, TYPE 1; ELECTROCARDIOGRAPHY; HEART RATE; HUMANS; HYPOGLYCEMIA; NEURAL NETWORKS (COMPUTER); SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 85009134597     PISSN: 1557170X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2016.7591483     Document Type: Conference Paper

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