Evidence map›Paper›PMID 31197243›Full record

ArticleScientific reports2019

An Unobtrusive and Calibration-free Blood Pressure Estimation Method using Photoplethysmography and Biometrics.

Xiaoman Xing, Zhimin Ma, Mingyou Zhang, Ying Zhou, Wenfei Dong, Mingxuan Song

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
39citing papers in PubMed, 1 pooled it
4.9field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

39 citing papers in PubMed, 1 synthesis or guideline pooled it, 96 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 1 country.

Xiaoman XingSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, 215163, China. xingxm@sibet.ac.cn.
Zhimin MaThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Science and Technology Town Hospital, Department of Endocrinology, Suzhou, Jiangsu, 215153, China.
Mingyou ZhangFirst Hospital of Jilin University, Cardiovascular Department, Changchun, Jilin, 130021, China.
Ying ZhouThe Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Science and Technology Town Hospital, Department of Endocrinology, Suzhou, Jiangsu, 215153, China.
Wenfei DongSuzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou, Jiangsu, 215163, China.
Mingxuan SongSuzhou GK Medical Co. Ltd, Suzhou, Jiangsu, 215163, China.
Chinese Academy of Sciences · CNNanjing Medical University · CNJilin University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We introduce a novel paradigm to unobtrusively and optically measure blood pressure (BP) without calibration. The algorithm combines photoplethysmography (PPG) waveform analysis and biometrics to estimate BP, and was evaluated in subjects with various age, height, weight and BP levels (n = 1249). In the young population (<50 years old) with low, medium and high systolic blood pressures (SBP, <120 mmHg; 120-139 mmHg; ≥140 mmHg), the fitting errors are 6.3 ± 7.2, -3.9 ± 7.2 and -20.2 ± 14.2 mmHg for SBP respectively; In the older population (>50 years old) with the same categories, the fitting errors are 12.8 ± 9.0, 0.5 ± 8.2 and -14.6 ± 11.5 mmHg for SBP respectively. A simple personalized calibration reduces fitting errors significantly (n = 147), and good peripheral perfusion helps to improve the fitting accuracy. In conclusion, PPG may be used to calculate BP without calibration in certain populations. When calibrated, it shows great potential to serially monitor BP fluctuation, which can bring tremendous economic and health benefits.

Indexed as

BiometryPhotoplethysmographyAdultAgedBlood PressureBlood Pressure DeterminationCalibrationHumansMiddle AgedPerfusionSystole

Identifiers

PMID31197243
PMCPMC6565722
OpenAlexW2952383525

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.