Evidence map›Paper›PMID 39184961›Full record

ArticleIEEE open journal of engineering in medicine and biology2024

A Review on Recent Advancements of Biomedical Radar for Clinical Applications.

Shuqin Dong, Li Wen, Yangtao Ye, Zhi Zhang, Yi Wang, Zhiwei Liu, Qing Cao, Yuchen Xu, Changzhi Li, Changzhan Gu

Abstract read
In one paragraph

Article in IEEE open journal of engineering in medicine and biology, 2024. 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
–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

9 citing papers in PubMed.

  1. Article
  2. Review
  3. Comparative Accuracy of Millimeter-Wave Radar and Polysomnography in Sleep Apnea Detection.Medical science monitor : international medical journal of experimental and clinical research · 2025
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Non-Contact Measurement of Cardiopulmonary Activity Using Software Defined Radios.IEEE journal of translational engineering in health and medicine · 2024
    Article
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

10 authors.

Shuqin DongState Key Laboratory of Radio Frequency Heterogeneous Integration and MoE Key Laboratory of Artificial IntelligenceShanghai Jiao Tong University Shanghai 200240 China.ORCID https://orcid.org/0000-0001-6875-0914
Li WenState Key Laboratory of Radio Frequency Heterogeneous Integration and MoE Key Laboratory of Artificial IntelligenceShanghai Jiao Tong University Shanghai 200240 China.ORCID https://orcid.org/0000-0003-4248-1503
Yangtao YeState Key Laboratory of Radio Frequency Heterogeneous Integration and MoE Key Laboratory of Artificial IntelligenceShanghai Jiao Tong University Shanghai 200240 China.ORCID https://orcid.org/0009-0009-9064-6297
Zhi ZhangShanghai General HospitalShanghai Jiao Tong University School of Medicine Shanghai 200080 China.ORCID https://orcid.org/0000-0002-0253-8192
Yi WangInternational Peace Maternity and Child Health HospitalShanghai Jiao Tong University School of Medicine Shanghai 200030 China.ORCID https://orcid.org/0009-0003-0324-1969
Zhiwei LiuInternational Peace Maternity and Child Health HospitalShanghai Jiao Tong University School of Medicine Shanghai 200030 China.ORCID https://orcid.org/0000-0003-4926-1319
Qing CaoRuijin HospitalShanghai Jiao Tong University School of Medicine Shanghai 200025 China.ORCID https://orcid.org/0000-0001-7557-9799
Yuchen XuRuijin HospitalShanghai Jiao Tong University School of Medicine Shanghai 200025 China.ORCID https://orcid.org/0009-0004-9732-071X
Changzhi LiDepartment of Electrical and Computer EngineeringTexas Tech University Lubbock TX 79409 USA.ORCID https://orcid.org/0000-0003-2188-4506
Changzhan GuState Key Laboratory of Radio Frequency Heterogeneous Integration and MoE Key Laboratory of Artificial IntelligenceShanghai Jiao Tong University Shanghai 200240 China.ORCID https://orcid.org/0000-0002-0224-9788

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The field of biomedical radar has witnessed significant advancements in recent years, paving the way for innovative and transformative applications in clinical settings. Most medical instruments invented to measure human activities rely on contact electrodes, causing discomfort. Thanks to its non-invasive nature, biomedical radar is particularly valuable for clinical applications. A significant portion of the review discusses improvements in radar hardware, with a focus on miniaturization, increased resolution, and enhanced sensitivity. Then, this paper also delves into the signal processing and machine learning techniques tailored for radar data. This review will explore the recent breakthroughs and applications of biomedical radar technology, shedding light on its transformative potential in shaping the future of clinical diagnostics, patient and elderly care, and healthcare innovation.

Indexed as

Biomedical radarcardiopulmonary activityclinical applicationdisplacement detectionmedical Internet of Things

Identifiers

PMID39184961
PMCPMC11342929

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.