Adjustment of basal insulin infusion rate in T1DM by hybrid PSO
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| 024 | 7 | 0 | |a 10.1007/s00500-014-1378-6 |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s00500-014-1378-6 | ||
| 245 | 0 | 0 | |a Adjustment of basal insulin infusion rate in T1DM by hybrid PSO |h [Elektronische Daten] |c [Zhijiang Lou, Bo Liu, Hongzhi Xie, Youqing Wang] |
| 520 | 3 | |a Basal insulin infusion rate which should be adjusted to increase or decrease insulin delivery with the varying blood sugar level plays a key role in type 1 diabetes mellitus (T1DM) patients for maintaining the blood glucose level approximately steady within reference range in order to avoid the complications developed from diabetes. This paper proposes an effective hybrid particle swarm optimization (HPSO) algorithm for solving the basal insulin infusion rate problem. In HPSO, bad experience lesson learning scheme and local search based on chaotic dynamics are proposed to make a good balance between global exploration and local exploitation. Simulation results based on a set of well-known optimization benchmark instances and the basal insulin infusion rate adjustment problem for T1DM demonstrate the effectiveness of the proposed HPSO. In silico tests on standard virtual subject via HPSO show that under nominal condition the blood glucose concentrations could be kept within a range of 80-150mg/dL within less than 5days; meanwhile, in case of random variations in meal timings within $$\pm $$ ± 60min or meal amounts within $$\pm $$ ± 75% deviation from the nominal values, the blood glucose concentrations could be kept within the safe regions. | |
| 540 | |a Springer-Verlag Berlin Heidelberg, 2014 | ||
| 690 | 7 | |a Particle swarm optimization (PSO) |2 nationallicence | |
| 690 | 7 | |a Glycemic control |2 nationallicence | |
| 690 | 7 | |a Basal insulin infusion rate optimization |2 nationallicence | |
| 690 | 7 | |a Type 1 diabetes mellitus |2 nationallicence | |
| 700 | 1 | |a Lou |D Zhijiang |u College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China |4 aut | |
| 700 | 1 | |a Liu |D Bo |u Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China |4 aut | |
| 700 | 1 | |a Xie |D Hongzhi |u College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China |4 aut | |
| 700 | 1 | |a Wang |D Youqing |u College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China |4 aut | |
| 773 | 0 | |t Soft Computing |d Springer Berlin Heidelberg |g 19/7(2015-07-01), 1921-1937 |x 1432-7643 |q 19:7<1921 |1 2015 |2 19 |o 500 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s00500-014-1378-6 |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s00500-014-1378-6 |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Lou |D Zhijiang |u College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Liu |D Bo |u Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Xie |D Hongzhi |u College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Wang |D Youqing |u College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Soft Computing |d Springer Berlin Heidelberg |g 19/7(2015-07-01), 1921-1937 |x 1432-7643 |q 19:7<1921 |1 2015 |2 19 |o 500 | ||