Intelligent infusion controller with a physiological information feedback function.


Journal

Technology and health care : official journal of the European Society for Engineering and Medicine
ISSN: 1878-7401
Titre abrégé: Technol Health Care
Pays: Netherlands
ID NLM: 9314590

Informations de publication

Date de publication:
2020
Historique:
pubmed: 5 5 2020
medline: 7 4 2021
entrez: 5 5 2020
Statut: ppublish

Résumé

In hospitals, some problems still exist, such as transfusion reaction that cannot be dealt with in time, medical staff cannot observe the physiological information of the infusion patients in real time, and the infusion speed cannot be controlled smartly. To address these problems, we propose a method for intelligent monitoring and designed a controller for dripping speed regulation. A photoelectric sensor was used to obtain the heart rate (HR) information, and a PID parameter self-tuning controller based on the fuzzy control principle was developed to establish a multi-stage adaptive control method based on HR feedback. By controlling the rotation of the motor to drive the cam to control the drip rate smartly. Also, the infusion and physiological information are transmitted to the nurse station to monitor the possible transfusion reaction. The experiments show that the intelligent infusion controller can achieve HR signal detection with an average accuracy of over 94%, dripping speed detection and adjustment with an average accuracy of above 98% and adjustment time within 35 seconds. Our study proved that the intelligent infusion controller can control the infusion process intelligently and effectively, and has excellent reliability, small steady-state error and high practical value.

Sections du résumé

BACKGROUND BACKGROUND
In hospitals, some problems still exist, such as transfusion reaction that cannot be dealt with in time, medical staff cannot observe the physiological information of the infusion patients in real time, and the infusion speed cannot be controlled smartly.
OBJECTIVE OBJECTIVE
To address these problems, we propose a method for intelligent monitoring and designed a controller for dripping speed regulation.
METHODS METHODS
A photoelectric sensor was used to obtain the heart rate (HR) information, and a PID parameter self-tuning controller based on the fuzzy control principle was developed to establish a multi-stage adaptive control method based on HR feedback. By controlling the rotation of the motor to drive the cam to control the drip rate smartly. Also, the infusion and physiological information are transmitted to the nurse station to monitor the possible transfusion reaction.
RESULTS RESULTS
The experiments show that the intelligent infusion controller can achieve HR signal detection with an average accuracy of over 94%, dripping speed detection and adjustment with an average accuracy of above 98% and adjustment time within 35 seconds.
CONCLUSION CONCLUSIONS
Our study proved that the intelligent infusion controller can control the infusion process intelligently and effectively, and has excellent reliability, small steady-state error and high practical value.

Identifiants

pubmed: 32364142
pii: THC209005
doi: 10.3233/THC-209005
pmc: PMC7369087
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

37-46

Références

Ann Hematol. 2010 Mar;89(3):309-16
pubmed: 19787352

Auteurs

Jing Li (J)

School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China.

Pengfei Dong (P)

School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China.

Yongxin Lai (Y)

School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China.

Xiansheng Qin (X)

School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China.

Jing Bai (J)

School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China.

Hongbo Wang (H)

School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China.

Zhanxi Wan (Z)

School of Mechanical Engineering, Northwestern Polytechnical University, Xi'an, Shaanxi, 710072, China.

Zhenyu Ji (Z)

Department of Medical Electronic Engineering, Faculty of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, 710032, China.

Xuetao Shi (X)

Department of Medical Electronic Engineering, Faculty of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, 710032, China.

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