Loading…
Simulation software for assessment of nonlinear and adaptive multivariable control algorithms: Glucose–insulin dynamics in Type 1 diabetes
A simulator for testing automatic control algorithms for nonlinear systems with time-varying parameters, variable time delays, and uncertainties is developed. It is based on simulation of virtual patients with Type 1 diabetes (T1D). Nonlinear models are developed to describe glucose concentration (G...
Saved in:
Published in: | Computers & chemical engineering 2019-11, Vol.130, p.106565, Article 106565 |
---|---|
Main Authors: | , , , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c520t-5e2445e72c4efd47d19afc7b1e1c43be0be114b18f7d93385c082f1575cde823 |
---|---|
cites | cdi_FETCH-LOGICAL-c520t-5e2445e72c4efd47d19afc7b1e1c43be0be114b18f7d93385c082f1575cde823 |
container_end_page | |
container_issue | |
container_start_page | 106565 |
container_title | Computers & chemical engineering |
container_volume | 130 |
creator | Rashid, Mudassir Samadi, Sediqeh Sevil, Mert Hajizadeh, Iman Kolodziej, Paul Hobbs, Nicole Maloney, Zacharie Brandt, Rachel Feng, Jianyuan Park, Minsun Quinn, Laurie Cinar, Ali |
description | A simulator for testing automatic control algorithms for nonlinear systems with time-varying parameters, variable time delays, and uncertainties is developed. It is based on simulation of virtual patients with Type 1 diabetes (T1D). Nonlinear models are developed to describe glucose concentration (GC) variations based on user-defined scenarios for meal consumption, insulin administration, and physical activity. They compute GC values and physiological variables, such as heart rate, skin temperature, accelerometer, and energy expenditure, that are indicative of physical activities affecting GC dynamics. This is the first simulator designed for assessment of multivariable controllers that consider supplemental physiological variables in addition to GC measurements to improve glycemic control. Virtual patients are generated from distributions of identified model parameters using clinical data. The simulator will enable testing and evaluation of new control algorithms proposed for automated insulin delivery as well as various control algorithms for nonlinear systems with uncertainties, time-varying parameters and delays. |
doi_str_mv | 10.1016/j.compchemeng.2019.106565 |
format | article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7449052</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0098135419307574</els_id><sourcerecordid>2438994559</sourcerecordid><originalsourceid>FETCH-LOGICAL-c520t-5e2445e72c4efd47d19afc7b1e1c43be0be114b18f7d93385c082f1575cde823</originalsourceid><addsrcrecordid>eNqNUb2OEzEQthCICwevgExHs8G_WS8FEorgQDqJgvSW155NHO3awfYGpeMB6HhDngRHOU5HRzWj8fczng-hV5QsKaGrN_uljdPB7mCCsF0yQrs6X8mVfIQWVLW8EbyVj9GCkE41lEtxhZ7lvCeEMKHUU3TFmVpx0bIF-vnVT_Noio8B5ziU7yYBHmLCJmfIuRoUHAccYhh9AFPnwWHjzKH4I-BKrdUkb_oRsI2hpDhiM25j8mU35bf4ZpxtzPD7xy8f8lw1sDsFM3mbce03pwNgil3lQ4H8HD0ZzJjhxV29RpuPHzbrT83tl5vP6_e3jZWMlEYCE0JCy6yAwYnW0c4Mtu0pUCt4D6QHSkVP1dC6jnMlLVFsoLKV1oFi_Bq9u8ge5n4CZ-sfkxn1IfnJpJOOxut_X4Lf6W086laIjsizwOs7gRS_zZCLnny2MI4mQJyzZoKrrhNSdhXaXaA2xZwTDPc2lOhzmHqvH4Spz2HqS5iV-_LhnvfMv-lVwPoCgHqso4eks_UQLDifwBbtov8Pmz-YX7z2</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2438994559</pqid></control><display><type>article</type><title>Simulation software for assessment of nonlinear and adaptive multivariable control algorithms: Glucose–insulin dynamics in Type 1 diabetes</title><source>ScienceDirect Journals</source><creator>Rashid, Mudassir ; Samadi, Sediqeh ; Sevil, Mert ; Hajizadeh, Iman ; Kolodziej, Paul ; Hobbs, Nicole ; Maloney, Zacharie ; Brandt, Rachel ; Feng, Jianyuan ; Park, Minsun ; Quinn, Laurie ; Cinar, Ali</creator><creatorcontrib>Rashid, Mudassir ; Samadi, Sediqeh ; Sevil, Mert ; Hajizadeh, Iman ; Kolodziej, Paul ; Hobbs, Nicole ; Maloney, Zacharie ; Brandt, Rachel ; Feng, Jianyuan ; Park, Minsun ; Quinn, Laurie ; Cinar, Ali</creatorcontrib><description>A simulator for testing automatic control algorithms for nonlinear systems with time-varying parameters, variable time delays, and uncertainties is developed. It is based on simulation of virtual patients with Type 1 diabetes (T1D). Nonlinear models are developed to describe glucose concentration (GC) variations based on user-defined scenarios for meal consumption, insulin administration, and physical activity. They compute GC values and physiological variables, such as heart rate, skin temperature, accelerometer, and energy expenditure, that are indicative of physical activities affecting GC dynamics. This is the first simulator designed for assessment of multivariable controllers that consider supplemental physiological variables in addition to GC measurements to improve glycemic control. Virtual patients are generated from distributions of identified model parameters using clinical data. The simulator will enable testing and evaluation of new control algorithms proposed for automated insulin delivery as well as various control algorithms for nonlinear systems with uncertainties, time-varying parameters and delays.</description><identifier>ISSN: 0098-1354</identifier><identifier>EISSN: 1873-4375</identifier><identifier>DOI: 10.1016/j.compchemeng.2019.106565</identifier><identifier>PMID: 32863472</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Benchmark testbed process ; Biomedical application ; Multivariable simulator ; Nonlinear and adaptive model predictive control ; Time-varying uncertain nonlinear system</subject><ispartof>Computers & chemical engineering, 2019-11, Vol.130, p.106565, Article 106565</ispartof><rights>2019</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c520t-5e2445e72c4efd47d19afc7b1e1c43be0be114b18f7d93385c082f1575cde823</citedby><cites>FETCH-LOGICAL-c520t-5e2445e72c4efd47d19afc7b1e1c43be0be114b18f7d93385c082f1575cde823</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32863472$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Rashid, Mudassir</creatorcontrib><creatorcontrib>Samadi, Sediqeh</creatorcontrib><creatorcontrib>Sevil, Mert</creatorcontrib><creatorcontrib>Hajizadeh, Iman</creatorcontrib><creatorcontrib>Kolodziej, Paul</creatorcontrib><creatorcontrib>Hobbs, Nicole</creatorcontrib><creatorcontrib>Maloney, Zacharie</creatorcontrib><creatorcontrib>Brandt, Rachel</creatorcontrib><creatorcontrib>Feng, Jianyuan</creatorcontrib><creatorcontrib>Park, Minsun</creatorcontrib><creatorcontrib>Quinn, Laurie</creatorcontrib><creatorcontrib>Cinar, Ali</creatorcontrib><title>Simulation software for assessment of nonlinear and adaptive multivariable control algorithms: Glucose–insulin dynamics in Type 1 diabetes</title><title>Computers & chemical engineering</title><addtitle>Comput Chem Eng</addtitle><description>A simulator for testing automatic control algorithms for nonlinear systems with time-varying parameters, variable time delays, and uncertainties is developed. It is based on simulation of virtual patients with Type 1 diabetes (T1D). Nonlinear models are developed to describe glucose concentration (GC) variations based on user-defined scenarios for meal consumption, insulin administration, and physical activity. They compute GC values and physiological variables, such as heart rate, skin temperature, accelerometer, and energy expenditure, that are indicative of physical activities affecting GC dynamics. This is the first simulator designed for assessment of multivariable controllers that consider supplemental physiological variables in addition to GC measurements to improve glycemic control. Virtual patients are generated from distributions of identified model parameters using clinical data. The simulator will enable testing and evaluation of new control algorithms proposed for automated insulin delivery as well as various control algorithms for nonlinear systems with uncertainties, time-varying parameters and delays.</description><subject>Benchmark testbed process</subject><subject>Biomedical application</subject><subject>Multivariable simulator</subject><subject>Nonlinear and adaptive model predictive control</subject><subject>Time-varying uncertain nonlinear system</subject><issn>0098-1354</issn><issn>1873-4375</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNqNUb2OEzEQthCICwevgExHs8G_WS8FEorgQDqJgvSW155NHO3awfYGpeMB6HhDngRHOU5HRzWj8fczng-hV5QsKaGrN_uljdPB7mCCsF0yQrs6X8mVfIQWVLW8EbyVj9GCkE41lEtxhZ7lvCeEMKHUU3TFmVpx0bIF-vnVT_Noio8B5ziU7yYBHmLCJmfIuRoUHAccYhh9AFPnwWHjzKH4I-BKrdUkb_oRsI2hpDhiM25j8mU35bf4ZpxtzPD7xy8f8lw1sDsFM3mbce03pwNgil3lQ4H8HD0ZzJjhxV29RpuPHzbrT83tl5vP6_e3jZWMlEYCE0JCy6yAwYnW0c4Mtu0pUCt4D6QHSkVP1dC6jnMlLVFsoLKV1oFi_Bq9u8ge5n4CZ-sfkxn1IfnJpJOOxut_X4Lf6W086laIjsizwOs7gRS_zZCLnny2MI4mQJyzZoKrrhNSdhXaXaA2xZwTDPc2lOhzmHqvH4Spz2HqS5iV-_LhnvfMv-lVwPoCgHqso4eks_UQLDifwBbtov8Pmz-YX7z2</recordid><startdate>20191102</startdate><enddate>20191102</enddate><creator>Rashid, Mudassir</creator><creator>Samadi, Sediqeh</creator><creator>Sevil, Mert</creator><creator>Hajizadeh, Iman</creator><creator>Kolodziej, Paul</creator><creator>Hobbs, Nicole</creator><creator>Maloney, Zacharie</creator><creator>Brandt, Rachel</creator><creator>Feng, Jianyuan</creator><creator>Park, Minsun</creator><creator>Quinn, Laurie</creator><creator>Cinar, Ali</creator><general>Elsevier Ltd</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20191102</creationdate><title>Simulation software for assessment of nonlinear and adaptive multivariable control algorithms: Glucose–insulin dynamics in Type 1 diabetes</title><author>Rashid, Mudassir ; Samadi, Sediqeh ; Sevil, Mert ; Hajizadeh, Iman ; Kolodziej, Paul ; Hobbs, Nicole ; Maloney, Zacharie ; Brandt, Rachel ; Feng, Jianyuan ; Park, Minsun ; Quinn, Laurie ; Cinar, Ali</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c520t-5e2445e72c4efd47d19afc7b1e1c43be0be114b18f7d93385c082f1575cde823</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Benchmark testbed process</topic><topic>Biomedical application</topic><topic>Multivariable simulator</topic><topic>Nonlinear and adaptive model predictive control</topic><topic>Time-varying uncertain nonlinear system</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rashid, Mudassir</creatorcontrib><creatorcontrib>Samadi, Sediqeh</creatorcontrib><creatorcontrib>Sevil, Mert</creatorcontrib><creatorcontrib>Hajizadeh, Iman</creatorcontrib><creatorcontrib>Kolodziej, Paul</creatorcontrib><creatorcontrib>Hobbs, Nicole</creatorcontrib><creatorcontrib>Maloney, Zacharie</creatorcontrib><creatorcontrib>Brandt, Rachel</creatorcontrib><creatorcontrib>Feng, Jianyuan</creatorcontrib><creatorcontrib>Park, Minsun</creatorcontrib><creatorcontrib>Quinn, Laurie</creatorcontrib><creatorcontrib>Cinar, Ali</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Computers & chemical engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rashid, Mudassir</au><au>Samadi, Sediqeh</au><au>Sevil, Mert</au><au>Hajizadeh, Iman</au><au>Kolodziej, Paul</au><au>Hobbs, Nicole</au><au>Maloney, Zacharie</au><au>Brandt, Rachel</au><au>Feng, Jianyuan</au><au>Park, Minsun</au><au>Quinn, Laurie</au><au>Cinar, Ali</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Simulation software for assessment of nonlinear and adaptive multivariable control algorithms: Glucose–insulin dynamics in Type 1 diabetes</atitle><jtitle>Computers & chemical engineering</jtitle><addtitle>Comput Chem Eng</addtitle><date>2019-11-02</date><risdate>2019</risdate><volume>130</volume><spage>106565</spage><pages>106565-</pages><artnum>106565</artnum><issn>0098-1354</issn><eissn>1873-4375</eissn><abstract>A simulator for testing automatic control algorithms for nonlinear systems with time-varying parameters, variable time delays, and uncertainties is developed. It is based on simulation of virtual patients with Type 1 diabetes (T1D). Nonlinear models are developed to describe glucose concentration (GC) variations based on user-defined scenarios for meal consumption, insulin administration, and physical activity. They compute GC values and physiological variables, such as heart rate, skin temperature, accelerometer, and energy expenditure, that are indicative of physical activities affecting GC dynamics. This is the first simulator designed for assessment of multivariable controllers that consider supplemental physiological variables in addition to GC measurements to improve glycemic control. Virtual patients are generated from distributions of identified model parameters using clinical data. The simulator will enable testing and evaluation of new control algorithms proposed for automated insulin delivery as well as various control algorithms for nonlinear systems with uncertainties, time-varying parameters and delays.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>32863472</pmid><doi>10.1016/j.compchemeng.2019.106565</doi><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0098-1354 |
ispartof | Computers & chemical engineering, 2019-11, Vol.130, p.106565, Article 106565 |
issn | 0098-1354 1873-4375 |
language | eng |
recordid | cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7449052 |
source | ScienceDirect Journals |
subjects | Benchmark testbed process Biomedical application Multivariable simulator Nonlinear and adaptive model predictive control Time-varying uncertain nonlinear system |
title | Simulation software for assessment of nonlinear and adaptive multivariable control algorithms: Glucose–insulin dynamics in Type 1 diabetes |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-23T08%3A45%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Simulation%20software%20for%20assessment%20of%20nonlinear%20and%20adaptive%20multivariable%20control%20algorithms:%20Glucose%E2%80%93insulin%20dynamics%20in%20Type%201%20diabetes&rft.jtitle=Computers%20&%20chemical%20engineering&rft.au=Rashid,%20Mudassir&rft.date=2019-11-02&rft.volume=130&rft.spage=106565&rft.pages=106565-&rft.artnum=106565&rft.issn=0098-1354&rft.eissn=1873-4375&rft_id=info:doi/10.1016/j.compchemeng.2019.106565&rft_dat=%3Cproquest_pubme%3E2438994559%3C/proquest_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c520t-5e2445e72c4efd47d19afc7b1e1c43be0be114b18f7d93385c082f1575cde823%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2438994559&rft_id=info:pmid/32863472&rfr_iscdi=true |