caa a22 4500 605469059 CHVBK 20210128100320.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00500-014-1378-6 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1378-6 Adjustment of basal insulin infusion rate in T1DM by hybrid PSO [Elektronische Daten] [Zhijiang Lou, Bo Liu, Hongzhi Xie, Youqing Wang] 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. Springer-Verlag Berlin Heidelberg, 2014 Particle swarm optimization (PSO) nationallicence Glycemic control nationallicence Basal insulin infusion rate optimization nationallicence Type 1 diabetes mellitus nationallicence Lou Zhijiang College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China aut Liu Bo Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China aut Xie Hongzhi College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China aut Wang Youqing College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China aut Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1921-1937 1432-7643 19:7<1921 2015 19 500 https://doi.org/10.1007/s00500-014-1378-6 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1378-6 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Lou Zhijiang College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China aut NATIONALLICENCE 700 1- Liu Bo Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China aut NATIONALLICENCE 700 1- Xie Hongzhi College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China aut NATIONALLICENCE 700 1- Wang Youqing College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1921-1937 1432-7643 19:7<1921 2015 19 500