Time series analysis and control of blood glucose levels in diabetic patients.
This paper describes features of a computer-based decision support system which is being developed to assist in the management of insulin-dependent diabetic patients. The clinical context is the provision of advice on the adjustment of the basic insulin regimen such as occurs at regular visits to the clinician. The integrated system combines data processing and interpretation, generation of qualitative advice and testing the implications of that advice using a glucose/insulin dynamic simulator. The two major features described in this paper are time series analysis of blood glucose data, and their interpretation in relation to the provision of advice for controlling the patient's blood glucose level. It is demonstrated that two approaches may be adopted in such time series analysis: an intuitive approach, manipulating symbolic representations of the data, and formal time series methods which decompose the series into clinically related components.
Deutsch
T
T
Department of Systems Science, City University, London, UK.
Lehmann
E D
ED
Carson
E R
ER
Roudsari
A V
AV
Hopkins
K D
KD
Sönksen
P H
PH
D001786:Blood Glucose / Q000378:metabolism*; D015190:Blood Glucose Self-Monitoring; D002940:Circadian Rhythm; D003658:Decision Making, Computer-Assisted; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000188:drug therapy*; D004334:Drug Administration Schedule; D001330:Electronic Data Processing; D005103:Expert Systems; D005246:Feedback; D005260:Female; D006801:Humans; D007328:Insulin / Q000008:administration & dosage; D008597:Menstrual Cycle / Q000502:physiology; D008875:Middle Aged; D013813:Therapy, Computer-Assisted
D001786:Blood Glucose; D007328:Insulin