Evidence map›Paper›PMID 34450945›Full record

ArticleSensors (Basel, Switzerland)2021

Contactless Simultaneous Breathing and Heart Rate Detections in Physical Activity Using IR-UWB Radars.

Xinyue Zhang, Xiuzhu Yang, Yi Ding, Yili Wang, Jialin Zhou, Lin Zhang

Abstract 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 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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.

Xinyue ZhangSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.ORCID 0000-0001-7623-731X
Xiuzhu YangSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Yi DingSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Yili WangSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Jialin ZhouSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Lin ZhangSchool of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing 100876, China.

Funding

National Natural Science Foundation of China 61971056Natural Science Foundation of Beijing Municipality 4192040
6 · The paper itself

Abstract

Vital signs monitoring in physical activity (PA) is of great significance in daily healthcare. Impulse Radio Ultra-WideBand (IR-UWB) radar provides a contactless vital signs detection approach with advantages in range resolution and penetration. Several researches have verified the feasibility of IR-UWB radar monitoring when the target keeps still. However, various body movements are induced by PA, which lead to severe signal distortion and interfere vital signs extraction. To address this challenge, a novel joint chest-abdomen cardiopulmonary signal estimation approach is proposed to detect breath and heartbeat simultaneously using IR-UWB radars. The movements of target chest and abdomen are detected by two IR-UWB radars, respectively. Considering the signal overlapping of vital signs and body motion artifacts, Empirical Wavelet Transform (EWT) is applied on received radar signals to remove clutter and mitigate movement interference. Moreover, improved EWT with frequency segmentation refinement is applied on each radar to decompose vital signals of target chest and abdomen to vital sign-related sub-signals, respectively. After that, based on the thoracoabdominal movement correlation, cross-correlation functions are calculated among chest and abdomen sub-signals to estimate breath and heartbeat. The experiments are conducted under three kinds of PA situations and two general body movements, the results of which indicate the effectiveness and superiority of the proposed approach.

Indexed as

RadarSignal Processing, Computer-AssistedAlgorithmsExerciseHeart RateVital SignsIR-UWB radarmovement interference alleviationphysical activityvital signs

Identifiers

PMID34450945
PMCPMC8402280

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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.