Significantly Reduced Blood Pressure Measurement Variability for Both Normotensive and Hypertensive Subjects: Effect of Polynomial Curve Fitting of Oscillometric Pulses

Author:

Yang Fangwei1ORCID,Chen Fei2ORCID,Zhu Mingping1,Chen Aiqing3,Zheng Dingchang3ORCID

Affiliation:

1. Department of Obstetrics and Gynecology, Yiwu Central Hospital, Yiwu, China

2. Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China

3. Health and Wellbeing Academy, Faculty of Medical Science, Anglia Ruskin University, Chelmsford, UK

Abstract

This study aimed to compare within-subject blood pressure (BP) variabilities from different measurement techniques. Cuff pressures from three repeated BP measurements were obtained from 30 normotensive and 30 hypertensive subjects. Automatic BPs were determined from the pulses with normalised peak amplitude larger than a threshold (0.5 for SBP, 0.7 for DBP, and 1.0 for MAP). They were also determined from cuff pressures associated with the above thresholds on a fitted curve polynomial curve of the oscillometric pulse peaks. Finally, the standard deviation (SD) of three repeats and its coefficient of variability (CV) were compared between the two automatic techniques. For the normotensive group, polynomial curve fitting significantly reduced SD of repeats from 3.6 to 2.5 mmHg for SBP and from 3.7 to 2.1 mmHg for MAP and reduced CV from 3.0% to 2.2% for SBP and from 4.3% to 2.4% for MAP (all P<0.01). For the hypertensive group, SD of repeats decreased from 6.5 to 5.5 mmHg for SBP and from 6.7 to 4.2 mmHg for MAP, and CV decreased from 4.2% to 3.6% for SBP and from 5.8% to 3.8% for MAP (all P<0.05). In conclusion, polynomial curve fitting of oscillometric pulses had the ability to reduce automatic BP measurement variability.

Funder

National Natural Science Foundation of China

Publisher

Hindawi Limited

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Blood Pressure Measurement Using a Gaussian Curve Fitting Algorithm;2022 29th National and 7th International Iranian Conference on Biomedical Engineering (ICBME);2022-12-21

2. A device employing a neural network for blood pressure estimation from the oscillatory pressure pulse wave and PPG signal;Sensor Review;2021-02-03

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