Evidence map›Paper›PMID 36458306›Full record

ArticleHeliyon2022

Noninvasive blood oxygen, heartbeat rate, and blood pressure parameter monitoring by photoplethysmography signals.

Chin-Jung Ku, Yuhling Wang, Chia-Yu Chang, Min-Tse Wu, Sheng-Tong Dai, Lun-De Liao

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 25% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
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  5. Review
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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 1 institution in 1 country.

Chin-Jung KuInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, No 35, Keyan Road, Zhunan Town, Miaoli County 350, Taiwan.
Yuhling WangInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, No 35, Keyan Road, Zhunan Town, Miaoli County 350, Taiwan.
Chia-Yu ChangInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, No 35, Keyan Road, Zhunan Town, Miaoli County 350, Taiwan.
Min-Tse WuInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, No 35, Keyan Road, Zhunan Town, Miaoli County 350, Taiwan.
Sheng-Tong DaiInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, No 35, Keyan Road, Zhunan Town, Miaoli County 350, Taiwan.
Lun-De LiaoInstitute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, No 35, Keyan Road, Zhunan Town, Miaoli County 350, Taiwan.
National Health Research Institutes · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The popularization of long-term invasive tools for continuously monitoring blood pressure remains challenging. However, with the rising popularity of wearable personal health management devices, non-cuff blood pressure measurement technology that applies electrocardiography (ECG) and photoplethysmography (PPG) has gradually received increasing attention. In particular, whether blood pressure can be measured continuously by the PPG signal alone is of great interest. In this study, we aim to develop a device that includes systolic and diastolic blood pressure calculation formulas derived from characteristic waveform points in the PPG time domain and that can measure blood oxygenation and heart rate. This device applies empirical formulas developed by PPG waveforms in the PhysioNet MIMIC-II database to calculate blood pressure. The systolic and diastolic pressures are then compared with the actual blood pressures obtained from invasive blood pressure waveforms to verify the effectiveness and feasibility of the complete developed system. Overall, 263 waveforms with double peaks and 261 waveforms with only a single peak totaling 524 sets of data are used to derive the empirical formulas. The systolic blood pressure estimation result using single peak analysis has an excessively large error exceeding ±40 mmHg, providing no reference value. However, systolic blood pressure estimation is notably better in double peak analysis, with error values reducing to approximately 23 mmHg. Diastolic pressure estimation errors are low with both single (±7 mmHg) and double peak (±4 mmHg) analyses. The error is lower in double-peak analysis than in single-peak analysis for obtaining systolic pressure from PPG waves. We plan to use PPG to detect additional physiological parameters in the future, e.g., respiratory rate, heart rate variability, or irregular heartbeat, to further enhance the functionality of PPG-based wearable devices.

Indexed as

Continuous blood pressureMIMIC-II databaseNoninvasivePhotoplethysmography

Identifiers

PMID36458306
PMCPMC9706696
OpenAlexW4309279730

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.