Evidence map›Paper›PMID 34770703›Full record

ArticleSensors (Basel, Switzerland)2021

Vital Signal Detection Using Multi-Radar for Reductions in Body Movement Effects.

Ah-Jung Jang, In-Seong Lee, Jong-Ryul Yang

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.8field-weighted citation impact, top 30% 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, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Pooled it
  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

3 authors at 1 institution in 1 country.

Ah-Jung JangDepartment of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Korea.ORCID 0000-0002-4679-7487
In-Seong LeeDepartment of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Korea.
Jong-Ryul YangDepartment of Electronic Engineering, Yeungnam University, Gyeongsan 38541, Korea.ORCID 0000-0003-4939-3274
Yeungnam University · KR

Funding

Yeungnam University 220A380046
6 · The paper itself

Abstract

Vital signal detection using multiple radars is proposed to reduce the signal degradation from a subject's body movement. The phase variation in the transceiving signals of continuous-wave radar due to respiration and heartbeat is generated by the body surface movement of the organs monitored in the line-of-sight (LOS) of the radar. The body movement signals obtained by two adjacent radars can be assumed to be the same over a certain distance. However, the vital signals are different in each radar, and each radar has a different LOS because of the asymmetric movement of lungs and heart. The proposed method uses two adjacent radars with different LOS to obtain correlated signals that reinforce the difference in the asymmetrical movement of the organs. The correlated signals can improve the signal-to-noise ratio in vital signal detection because of a reduction in the body movement effect. Two radars at different frequencies in the 5.8 GHz band are implemented to reduce direct signal coupling. Measurement results using the radars arranged at angles of 30°, 45°, and 60° showed that the proposed method can detect the vital signals with a mean accuracy of 97.8% for the subject moving at a maximum velocity of 53.4 mm/s.

Indexed as

RadarSignal Processing, Computer-AssistedHeart RateMonitoring, PhysiologicRespirationbody movement cancelationcontinuous waveDoppler radarheartbeatmultiple radarsrespirationvital signal detection

Identifiers

PMID34770703
PMCPMC8587079
OpenAlexW3212036220

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.