Evidence map›Paper›PMID 36831957›Full record

ArticleBiosensors2023

A Feasibility Study of Remote Non-Contact Vital Signs (NCVS) Monitoring in a Clinic Using a Novel Sensor Realized by Software-Defined Radio (SDR).

Yang Liu, Clint Sweeney, Jill C Mayeda, Jerry Lopez, Paul E Lie, Tam Q Nguyen, Donald Y C Lie

Open access · goldAbstract read
In one paragraph

Article in Biosensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 37% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Review
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 1 institution in 1 country.

Yang LiuDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79430, USA.ORCID 0000-0002-5686-2801
Clint SweeneyDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79430, USA.
Jill C MayedaDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79430, USA.
Jerry LopezDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79430, USA.
Paul E LieTexas Tech University Health Sciences Center (TTUHSC), Texas Tech University, Lubbock, TX 79430, USA.
Tam Q NguyenDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79430, USA.
Donald Y C LieDepartment of Electrical and Computer Engineering, Texas Tech University, Lubbock, TX 79430, USA.ORCID 0000-0002-1788-8910
Texas Tech University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 outbreak has caused panic around the world as it is highly infectious and has caused about 5 million deaths globally. A robust wireless non-contact vital signs (NCVS) sensor system that can continuously monitor the respiration rate (RR) and heart rate (HR) of patients clinically and remotely with high accuracy can be very attractive to healthcare workers (HCWs), as such a system can not only avoid HCWs' close contact with people with COVID-19 to reduce the infection rate, but also be used on patients quarantined at home for telemedicine and wireless acute-care. Therefore, we developed a custom Doppler-based NCVS radar sensor system operating at 2.4 GHz using a software-defined radio (SDR) technology, and the novel biosensor system has achieved impressive real-time RR/HR monitoring accuracies within approximately 0.5/3 breath/beat per minute (BPM) on student volunteers tested in our engineering labs. To further test the sensor system's feasibility for clinical use, we applied and obtained an Internal Review Board (IRB) approval from Texas Tech University Health Sciences Center (TTUHSC) and have used this NCVS monitoring system in a doctor's clinic at TTUHSC; following testing on 20 actual patients for a small-scale clinical trial, we have found that the system was still able to achieve good NCVS monitoring accuracies within ~0.5/10 BPM across 20 patients of various weight, height and age. These results suggest our custom-designed NCVS monitoring system may be feasible for future clinical use to help combatting COVID-19 and other infectious diseases.

Indexed as

COVID-19Feasibility StudiesHeart RateHumansMonitoring, PhysiologicRespiratory RateSoftwareVital SignsbiosensorCOVID-19non-contact vital signs (NCVS)respiration rate (RR)software-defined radio (SDR)telemedicinewireless acute carewireless assisted living

Identifiers

PMID36831957
PMCPMC9953371
OpenAlexW4318476512

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.