Sun, Qingnan; Jankovic, Marko; Mougiakakou, Stavroula (20 November 2018). Impact of Errors in Carbohydrate Estimation on Control of Blood Glucose in Type 1 Diabetes (In Press). In: 2018 14th IEEE Symposium on Neural Networks and Applications (NEUREL) - IEEE Neurel2018. Institute of Electrical and Electronics Engineers
Full text not available from this repository.This article investigates the impact of carbohydrate (CHO) estimation error on three different
algorithms for insulin treatment optimisation. The experiments were conducted using the educational version of the UVa/Padova simulator on 11 virtual adult subjects. Under different CHO estimation error levels, two ways of CHO amount announcements were investigated: numerical value and categorical value (Small, Medium, and Large). Results of experiments suggest that by low CHO estimation error, the way of CHO level announcement has low impact
on algorithm quality. As the error increases more intelligent algorithmic approaches need to be investigated.
Item Type: |
Conference or Workshop Item (Paper) |
|---|---|
Division/Institute: |
10 Strategic Research Centers > ARTORG Center for Biomedical Engineering Research > ARTORG Center - AI in Health and Nutrition 04 Faculty of Medicine > Department of Intensive Care, Emergency Medicine and Anaesthesiology (DINA) > University Emergency Center |
Graduate School: |
Graduate School for Cellular and Biomedical Sciences (GCB) |
UniBE Contributor: |
Sun, Qingnan, Jankovic, Marko, Mougiakakou, Stavroula |
Subjects: |
600 Technology > 610 Medicine & health 600 Technology > 620 Engineering |
Publisher: |
Institute of Electrical and Electronics Engineers |
Language: |
English |
Submitter: |
Stavroula Mougiakakou |
Date Deposited: |
21 Nov 2018 12:55 |
Last Modified: |
05 Dec 2022 15:19 |
URI: |
https://boris.unibe.ch/id/eprint/121322 |
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