Evidence map›Paper›PMID 31266256›Full record

ArticleSensors (Basel, Switzerland)2019

Unobtrusive Estimation of Cardiovascular Parameters with Limb Ballistocardiography.

Yang Yao, Sungtae Shin, Azin Mousavi, Chang-Sei Kim, Lisheng Xu, Ramakrishna Mukkamala, Jin-Oh Hahn

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.0field-weighted citation impact, top 14% 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

9 citing papers in PubMed, 33 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

7 authors at 4 institutions in 3 countries.

Yang YaoCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China.ORCID 0000-0001-8129-3076
Sungtae ShinDepartment of Mechanical Engineering, University of Maryland, College Park, College Park, MD 20742, USA.ORCID 0000-0002-9054-5666
Azin MousaviDepartment of Mechanical Engineering, University of Maryland, College Park, College Park, MD 20742, USA.ORCID 0000-0002-2886-5642
Chang-Sei KimSchool of Mechanical Engineering, Chonnam National University, Gwangju 61186, Korea.
Lisheng XuCollege of Medicine and Biological Information Engineering, Northeastern University, Shenyang 110169, China.
Ramakrishna MukkamalaDepartment of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA.ORCID 0000-0001-8918-4050
Jin-Oh HahnDepartment of Mechanical Engineering, University of Maryland, College Park, College Park, MD 20742, USA. jhahn12@umd.edu.ORCID 0000-0001-5429-2836
University of Maryland, College Park · USChonnam National University · KRMichigan State University · USNortheastern University · CN

Funding

China Scholarship Council N/ANational Natural Science Foundation of China 61773110University of Maryland UM Ventures Seed Grant
6 · The paper itself

Abstract

This study investigates the potential of the limb ballistocardiogram (BCG) for unobtrusive estimation of cardiovascular (CV) parameters. In conjunction with the reference CV parameters (including diastolic, pulse, and systolic pressures, stroke volume, cardiac output, and total peripheral resistance), an upper-limb BCG based on an accelerometer embedded in a wearable armband and a lower-limb BCG based on a strain gauge embedded in a weighing scale were instrumented simultaneously with a finger photoplethysmogram (PPG). To standardize the analysis, the more convenient yet unconventional armband BCG was transformed into the more conventional weighing scale BCG (called the synthetic weighing scale BCG) using a signal processing procedure. The characteristic features were extracted from these BCG and PPG waveforms in the form of wave-to-wave time intervals, wave amplitudes, and wave-to-wave amplitudes. Then, the relationship between the characteristic features associated with (i) the weighing scale BCG-PPG pair and (ii) the synthetic weighing scale BCG-PPG pair versus the CV parameters, was analyzed using the multivariate linear regression analysis. The results indicated that each of the CV parameters of interest may be accurately estimated by a combination of as few as two characteristic features in the upper-limb or lower-limb BCG, and also that the characteristic features recruited for the CV parameters were to a large extent relevant according to the physiological mechanism underlying the BCG.

Indexed as

Signal Processing, Computer-AssistedAdultBallistocardiographyBlood PressureCardiovascular Physiological PhenomenaCardiovascular SystemElectrocardiographyExtremitiesFemaleHealthy VolunteersHeart RateHumansMalePhotoplethysmographyStroke Volumeballistocardiogramballistocardiographyblood pressurecardiac outputphotoplethysmogramphotoplethysmographystroke volumetotal peripheral resistance

Identifiers

PMID31266256
PMCPMC6651596
OpenAlexW2955541794

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.