Evidence map›Paper›PMID 37435306›Full record

ArticleFrontiers in physiology2023

A novel target state detection method for accurate cardiopulmonary signal extraction based on FMCW radar signals.

Xiaozheng Zhang, Chenxi Yang, Zhengyu Xiao, Binbin Lu, Ji Zhang, Jianqing Li, Chengyu Liu

Abstract read
In one paragraph

Article in Frontiers in physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Xiaozheng ZhangThe State Key Laboratory of Digital Medical Engineering, School of Instrument Science and Engineering, Southeast University, Nanjing, China.
Chenxi YangThe State Key Laboratory of Digital Medical Engineering, School of Instrument Science and Engineering, Southeast University, Nanjing, China.
Zhengyu XiaoChuhang Technology Co. Ltd., Nanjing, China.
Binbin LuChuhang Technology Co. Ltd., Nanjing, China.
Ji ZhangChuhang Technology Co. Ltd., Nanjing, China.
Jianqing LiThe State Key Laboratory of Digital Medical Engineering, School of Instrument Science and Engineering, Southeast University, Nanjing, China.
Chengyu LiuThe State Key Laboratory of Digital Medical Engineering, School of Instrument Science and Engineering, Southeast University, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Frequency-modulated continuous wave radar is capable of constant, real-time detection of human presence and monitoring of cardiopulmonary signals such as respiration and heartbeat. In highly cluttered environments or when the human body moves randomly, noise signals may be relatively large in some range bins, making it crucial to accurately select the range bin containing the target cardiopulmonary signal. In this paper, we propose a target range bin selection algorithm based on a mixed-modal information threshold. We introduce a confidence value in the frequency domain to determine the state of the human target and employ the range bin variance in the time domain to determine the range bin change status of the target. The proposed method accurately detects the state of the target and effectively selects the range bin containing the cardiopulmonary signal with a high signal-to-noise ratio. Experimental results demonstrate that the proposed method achieves better accuracy in cardiopulmonary signal rate estimation. Moreover, the proposed algorithm is lightweight in data processing and has good real-time performance.

Indexed as

cardiopulmonary signalFMCW radarheart raterange binrespiration ratetarget state detection

Identifiers

PMID37435306
PMCPMC10330764

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.