Abstract
Objective: This paper aims to develop an algorithm that can detect unannounced meals and estimate meal sizes to achieve a robust glucose control. Methods: A variable state dimension (VSD) algorithm is developed to detect unannounced meals and estimate meal sizes, where a Kalman filter operates on a quiescent state model when no meal is detected, and switches to a maneuvering state model to estimate meal information once the meal-induced glucose variability is statistically significant. Results: Through evaluation using 30 subjects of the UVa/Padova simulator, a basal-bolus (BB) control using the VSD-estimated meal size for each meal can achieve mean blood glucose (BG) of 142 mg/dl with an average 17.7% of time in hypoglycemia. In terms of 20 Monte-Carlo simulations for each subject over a two-day scenario, where each meal/snack has a probability of 0.5 not to be announced, the BB control using VSD for unannounced meals can achieve an average mean BG of 143 mg/dl with 8% of time in hypoglycemia, in contrast to mean BG of 180 mg/dl with 8% of time in hypoglycemia obtained by BB with missing boluses. Additionally, VSD is able to detect a meal within 45 (±14) min since its start with a 76% success rate and 16% false alarm rate. Conclusion: The addition of VSD to the BB control improves glucose control when meal announcements are missed. Significance: The VSD can be used as a complementary tool to detect meal and estimate meal size in absence of a meal announcement.
| Original language | English (US) |
|---|---|
| Article number | 7539656 |
| Pages (from-to) | 1249-1260 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Biomedical Engineering |
| Volume | 64 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jun 2017 |
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All Science Journal Classification (ASJC) codes
- Biomedical Engineering
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A variable state dimension approach to meal detection and meal size estimation : In silico evaluation through basal-bolus insulin therapy for type 1 diabetes. / Xie, Jinyu; Wang, Qian.
In: IEEE Transactions on Biomedical Engineering, Vol. 64, No. 6, 7539656, 06.2017, p. 1249-1260.Research output: Contribution to journal › Article
TY - JOUR
T1 - A variable state dimension approach to meal detection and meal size estimation
T2 - In silico evaluation through basal-bolus insulin therapy for type 1 diabetes
AU - Xie, Jinyu
AU - Wang, Qian
PY - 2017/6
Y1 - 2017/6
N2 - Objective: This paper aims to develop an algorithm that can detect unannounced meals and estimate meal sizes to achieve a robust glucose control. Methods: A variable state dimension (VSD) algorithm is developed to detect unannounced meals and estimate meal sizes, where a Kalman filter operates on a quiescent state model when no meal is detected, and switches to a maneuvering state model to estimate meal information once the meal-induced glucose variability is statistically significant. Results: Through evaluation using 30 subjects of the UVa/Padova simulator, a basal-bolus (BB) control using the VSD-estimated meal size for each meal can achieve mean blood glucose (BG) of 142 mg/dl with an average 17.7% of time in hypoglycemia. In terms of 20 Monte-Carlo simulations for each subject over a two-day scenario, where each meal/snack has a probability of 0.5 not to be announced, the BB control using VSD for unannounced meals can achieve an average mean BG of 143 mg/dl with 8% of time in hypoglycemia, in contrast to mean BG of 180 mg/dl with 8% of time in hypoglycemia obtained by BB with missing boluses. Additionally, VSD is able to detect a meal within 45 (±14) min since its start with a 76% success rate and 16% false alarm rate. Conclusion: The addition of VSD to the BB control improves glucose control when meal announcements are missed. Significance: The VSD can be used as a complementary tool to detect meal and estimate meal size in absence of a meal announcement.
AB - Objective: This paper aims to develop an algorithm that can detect unannounced meals and estimate meal sizes to achieve a robust glucose control. Methods: A variable state dimension (VSD) algorithm is developed to detect unannounced meals and estimate meal sizes, where a Kalman filter operates on a quiescent state model when no meal is detected, and switches to a maneuvering state model to estimate meal information once the meal-induced glucose variability is statistically significant. Results: Through evaluation using 30 subjects of the UVa/Padova simulator, a basal-bolus (BB) control using the VSD-estimated meal size for each meal can achieve mean blood glucose (BG) of 142 mg/dl with an average 17.7% of time in hypoglycemia. In terms of 20 Monte-Carlo simulations for each subject over a two-day scenario, where each meal/snack has a probability of 0.5 not to be announced, the BB control using VSD for unannounced meals can achieve an average mean BG of 143 mg/dl with 8% of time in hypoglycemia, in contrast to mean BG of 180 mg/dl with 8% of time in hypoglycemia obtained by BB with missing boluses. Additionally, VSD is able to detect a meal within 45 (±14) min since its start with a 76% success rate and 16% false alarm rate. Conclusion: The addition of VSD to the BB control improves glucose control when meal announcements are missed. Significance: The VSD can be used as a complementary tool to detect meal and estimate meal size in absence of a meal announcement.
UR - http://www.scopus.com/inward/record.url?scp=85021682704&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85021682704&partnerID=8YFLogxK
U2 - 10.1109/TBME.2016.2599073
DO - 10.1109/TBME.2016.2599073
M3 - Article
C2 - 28541188
AN - SCOPUS:85021682704
VL - 64
SP - 1249
EP - 1260
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
SN - 0018-9294
IS - 6
M1 - 7539656
ER -