TY - GEN
T1 - An information and communication technology system to detect hypoglycemia in people with type 1 diabetes
AU - Jensen, Morten Hasselstrøm
AU - Christensen, Toke Folke
AU - Tarnow, Lise
AU - Johansen, Mette Dencker
AU - Hejlesen, Ole Kristian
PY - 2013/1/1
Y1 - 2013/1/1
N2 - Continuous glucose monitoring (CGM) is a new technology with the potential to detect hypoglycemia in people with Type 1 diabetes. However, the inaccuracy of the device in the hypoglycemic range is unfortunately too large. The aim of this study was to develop an information and communication technology system for improving hypoglycemia detection in CGM. The system was developed as an Android application with a build-in pattern classification algorithm. The algorithm processes features from CGM and typed in data from the patient, then warns the patient about incoming hypoglycemia. The system improved the detection of hypoglycemic events by 29%, with only one 1 false alert compared to CGM alone. Furthermore, the algorithm increased the average lead-time by 14 minutes. These findings indicate that it is possible to improve the hypoglycemia detection with an information and communication technology system, but that the system must be validated on a larger dataset.
AB - Continuous glucose monitoring (CGM) is a new technology with the potential to detect hypoglycemia in people with Type 1 diabetes. However, the inaccuracy of the device in the hypoglycemic range is unfortunately too large. The aim of this study was to develop an information and communication technology system for improving hypoglycemia detection in CGM. The system was developed as an Android application with a build-in pattern classification algorithm. The algorithm processes features from CGM and typed in data from the patient, then warns the patient about incoming hypoglycemia. The system improved the detection of hypoglycemic events by 29%, with only one 1 false alert compared to CGM alone. Furthermore, the algorithm increased the average lead-time by 14 minutes. These findings indicate that it is possible to improve the hypoglycemia detection with an information and communication technology system, but that the system must be validated on a larger dataset.
KW - Diabetes
KW - hypoglycemia
KW - medical informatics application
KW - pattern recognition
UR - https://www.scopus.com/pages/publications/84894316211
U2 - 10.3233/978-1-61499-289-9-38
DO - 10.3233/978-1-61499-289-9-38
M3 - Conference contribution
C2 - 23920511
AN - SCOPUS:84894316211
SN - 9781614992882
T3 - Studies in Health Technology and Informatics
SP - 38
EP - 41
BT - MEDINFO 2013 - Proceedings of the 14th World Congress on Medical and Health Informatics
PB - IOS Press
T2 - 14th World Congress on Medical and Health Informatics, MEDINFO 2013
Y2 - 20 August 2013 through 23 August 2013
ER -