Evidence map›Paper›PMID 37248245›Full record

ArticleScientific reports2023

Ultra-low-cost mechanical smartphone attachment for no-calibration blood pressure measurement.

Yinan Xuan, Colin Barry, Jessica De Souza, Jessica H Wen, Nick Antipa, Alison A Moore, Edward J Wang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. A Touch Enabled Hemodynamic and Metabolic Monitor.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  4. Review
  5. Article
  6. Article
  7. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Yinan XuanElectrical and Computer Engineering Department, UC San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA. yxuan@ucsd.edu.
Colin BarryElectrical and Computer Engineering Department, UC San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA.
Jessica De SouzaElectrical and Computer Engineering Department, UC San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA.
Jessica H WenDepartment of Medicine, UC San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA.
Nick AntipaElectrical and Computer Engineering Department, UC San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA.
Alison A MooreDepartment of Medicine, UC San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA.
Edward J WangElectrical and Computer Engineering Department, UC San Diego, 9500 Gilman Dr., La Jolla, CA, 92093, USA. ejaywang@eng.ucsd.edu.
University of California, San Diego · US

Funding

Validating novel sleep sensors and devices in older adults with Alzheimer's diseaseP30AG073107 · NIA · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Sudeshna Das · 2021 to 2026
$32.0M
NIA NIH HHS MassAITC P30AG073107 Subaward 23-016677 N 00
6 · The paper itself

Abstract

We propose an ultra-low-cost at-home blood pressure monitor that leverages a plastic clip with a spring-loaded mechanism to enable a smartphone with a flash LED and camera to measure blood pressure. Our system, called BPClip, is based on the scientific premise of measuring oscillometry at the fingertip to measure blood pressure. To enable a smartphone to measure the pressure applied to the digital artery, a moveable pinhole projection moves closer to the camera as the user presses down on the clip with increased force. As a user presses on the device with increased force, the spring-loaded mechanism compresses. The size of the pinhole thus encodes the pressure applied to the finger. In conjunction, the brightness fluctuation of the pinhole projection correlates to the arterial pulse amplitude. By capturing the size and brightness of the pinhole projection with the built-in camera, the smartphone can measure a user's blood pressure with only a low-cost, plastic clip and an app. Unlike prior approaches, this system does not require a blood pressure cuff measurement for a user-specific calibration compared to pulse transit time and pulse wave analysis based blood pressure monitoring solutions. Our solution also does not require specialized smartphone models with custom sensors. Our early feasibility finding demonstrates that in a validation study with N = 29 participants with systolic blood pressures ranging from 88 to 157 mmHg, the BPClip system can achieve a mean absolute error of 8.72 and 5.49 for systolic and diastolic blood pressure, respectively. In an estimated cost projection study, we demonstrate that in small-batch manufacturing of 1000 units, the material cost is an estimated $0.80, suggesting that at full-scale production, our proposed BPClip concept can be produced at very low cost compared to existing cuff-based monitors for at-home blood pressure management.

Indexed as

Blood Pressure DeterminationSmartphoneBlood PressureBlood Pressure MonitorsCalibrationHumansPulse Wave Analysis

Identifiers

PMID37248245
PMCPMC10227087
OpenAlexW4378715465

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.