Study on insulin infusion estimation based on continuous blood glucose data

Weijie Wang; Shaoping Wang; Yixuan Geng; Dengao Li; Shiwei Liu

doi:10.1109/ICIEA58696.2023.10241578

Study on insulin infusion estimation based on continuous blood glucose data

Weijie Wang^*
, Shaoping Wang
, Yixuan Geng
, Dengao Li
, Shiwei Liu^*

^*Corresponding author for this work

School of Automation Science and Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Insulin pump is the key equipment for intensive insulin treatment of diabetes, but it often has failures such as tube blockage and leaking tubes. Such failures can lead to insufficient insulin infusions, which make it difficult for patients to lower blood glucose and endanger the health. Estimating the insulin infusion is helpful for fault diagnosis of insulin pumps. This paper proposes a method for estimating insulin infusion based on dynamic blood glucose data. Firstly, a glucose-insulin model is built based on physiological mechanisms. Secondly, a particle filter estimator is established. Finally, based on the monitored glucose data, insulin infusion is estimated dynamically. It is verified by simulation that the method can estimate the real insulin infusion rate effectively. The method has the potential to provide a path for insulin pump fault diagnosis.

Original language	English
Title of host publication	Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023
Editors	Wenjian Cai, Guilin Yang, Jun Qiu, Tingting Gao, Lijun Jiang, Tianjiang Zheng, Xinli Wang
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1620-1625
Number of pages	6
ISBN (Electronic)	9798350312201
DOIs	https://doi.org/10.1109/ICIEA58696.2023.10241578
State	Published - 2023
Event	18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023 - Ningbo, China Duration: 18 Aug 2023 → 22 Aug 2023

Publication series

Name	Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

Conference

Conference	18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023
Country/Territory	China
City	Ningbo
Period	18/08/23 → 22/08/23

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

failure diagnosis
insulin pump
particle filter

Access to Document

10.1109/ICIEA58696.2023.10241578

Cite this

Wang, W., Wang, S., Geng, Y., Li, D., & Liu, S. (2023). Study on insulin infusion estimation based on continuous blood glucose data. In W. Cai, G. Yang, J. Qiu, T. Gao, L. Jiang, T. Zheng, & X. Wang (Eds.), Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023 (pp. 1620-1625). (Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICIEA58696.2023.10241578

Wang, Weijie ; Wang, Shaoping ; Geng, Yixuan et al. / Study on insulin infusion estimation based on continuous blood glucose data. Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023. editor / Wenjian Cai ; Guilin Yang ; Jun Qiu ; Tingting Gao ; Lijun Jiang ; Tianjiang Zheng ; Xinli Wang. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 1620-1625 (Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023).

@inproceedings{66dffe5bf2fa43df962893a4b4398d1a,

title = "Study on insulin infusion estimation based on continuous blood glucose data",

abstract = "Insulin pump is the key equipment for intensive insulin treatment of diabetes, but it often has failures such as tube blockage and leaking tubes. Such failures can lead to insufficient insulin infusions, which make it difficult for patients to lower blood glucose and endanger the health. Estimating the insulin infusion is helpful for fault diagnosis of insulin pumps. This paper proposes a method for estimating insulin infusion based on dynamic blood glucose data. Firstly, a glucose-insulin model is built based on physiological mechanisms. Secondly, a particle filter estimator is established. Finally, based on the monitored glucose data, insulin infusion is estimated dynamically. It is verified by simulation that the method can estimate the real insulin infusion rate effectively. The method has the potential to provide a path for insulin pump fault diagnosis.",

keywords = "failure diagnosis, insulin pump, particle filter",

author = "Weijie Wang and Shaoping Wang and Yixuan Geng and Dengao Li and Shiwei Liu",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023 ; Conference date: 18-08-2023 Through 22-08-2023",

year = "2023",

doi = "10.1109/ICIEA58696.2023.10241578",

language = "英语",

series = "Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1620--1625",

editor = "Wenjian Cai and Guilin Yang and Jun Qiu and Tingting Gao and Lijun Jiang and Tianjiang Zheng and Xinli Wang",

booktitle = "Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023",

address = "美国",

}

Wang, W, Wang, S, Geng, Y, Li, D & Liu, S 2023, Study on insulin infusion estimation based on continuous blood glucose data. in W Cai, G Yang, J Qiu, T Gao, L Jiang, T Zheng & X Wang (eds), Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023. Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023, Institute of Electrical and Electronics Engineers Inc., pp. 1620-1625, 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023, Ningbo, China, 18/08/23. https://doi.org/10.1109/ICIEA58696.2023.10241578

Study on insulin infusion estimation based on continuous blood glucose data. / Wang, Weijie; Wang, Shaoping; Geng, Yixuan et al.
Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023. ed. / Wenjian Cai; Guilin Yang; Jun Qiu; Tingting Gao; Lijun Jiang; Tianjiang Zheng; Xinli Wang. Institute of Electrical and Electronics Engineers Inc., 2023. p. 1620-1625 (Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Study on insulin infusion estimation based on continuous blood glucose data

AU - Wang, Weijie

AU - Wang, Shaoping

AU - Geng, Yixuan

AU - Li, Dengao

AU - Liu, Shiwei

PY - 2023

Y1 - 2023

N2 - Insulin pump is the key equipment for intensive insulin treatment of diabetes, but it often has failures such as tube blockage and leaking tubes. Such failures can lead to insufficient insulin infusions, which make it difficult for patients to lower blood glucose and endanger the health. Estimating the insulin infusion is helpful for fault diagnosis of insulin pumps. This paper proposes a method for estimating insulin infusion based on dynamic blood glucose data. Firstly, a glucose-insulin model is built based on physiological mechanisms. Secondly, a particle filter estimator is established. Finally, based on the monitored glucose data, insulin infusion is estimated dynamically. It is verified by simulation that the method can estimate the real insulin infusion rate effectively. The method has the potential to provide a path for insulin pump fault diagnosis.

AB - Insulin pump is the key equipment for intensive insulin treatment of diabetes, but it often has failures such as tube blockage and leaking tubes. Such failures can lead to insufficient insulin infusions, which make it difficult for patients to lower blood glucose and endanger the health. Estimating the insulin infusion is helpful for fault diagnosis of insulin pumps. This paper proposes a method for estimating insulin infusion based on dynamic blood glucose data. Firstly, a glucose-insulin model is built based on physiological mechanisms. Secondly, a particle filter estimator is established. Finally, based on the monitored glucose data, insulin infusion is estimated dynamically. It is verified by simulation that the method can estimate the real insulin infusion rate effectively. The method has the potential to provide a path for insulin pump fault diagnosis.

KW - failure diagnosis

KW - insulin pump

KW - particle filter

UR - https://www.scopus.com/pages/publications/85173610325

U2 - 10.1109/ICIEA58696.2023.10241578

DO - 10.1109/ICIEA58696.2023.10241578

M3 - 会议稿件

AN - SCOPUS:85173610325

T3 - Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

SP - 1620

EP - 1625

BT - Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

A2 - Cai, Wenjian

A2 - Yang, Guilin

A2 - Qiu, Jun

A2 - Gao, Tingting

A2 - Jiang, Lijun

A2 - Zheng, Tianjiang

A2 - Wang, Xinli

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

Y2 - 18 August 2023 through 22 August 2023

ER -

Wang W, Wang S, Geng Y, Li D, Liu S. Study on insulin infusion estimation based on continuous blood glucose data. In Cai W, Yang G, Qiu J, Gao T, Jiang L, Zheng T, Wang X, editors, Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 1620-1625. (Proceedings of the 18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023). doi: 10.1109/ICIEA58696.2023.10241578

Study on insulin infusion estimation based on continuous blood glucose data

Abstract

Publication series

Conference

UN SDGs

Keywords

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