Evidence map›Paper›PMID 42032310›Full record

Articlenpj biomedical innovations2026

Contactless 12-lead electrocardiogram via deep computational radar.

Zhi Lu, Jinbo Chen, Dongheng Zhang, Haoyu Wang, Pengcheng Huang, Fang Zhou, Yang Hu, Qibin Sun, Min Gao, Yan Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in npj biomedical innovations, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

10 authors.

Zhi Lu *School of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.
Jinbo Chen *School of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.
Dongheng ZhangSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.
Haoyu WangSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.
Pengcheng HuangSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.
Fang ZhouSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.
Yang HuSchool of Information Science and Technology, University of Science and Technology of China, Hefei, Anhui, China. eeyhu@ustc.edu.cn.
Qibin SunSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China.
Min GaoThe First Affiliated Hospital of USTC, University of Science and Technology of China, Hefei, Anhui, China. gm197866@mail.ustc.edu.cn.
Yan ChenSchool of Cyber Science and Technology, University of Science and Technology of China, Hefei, Anhui, China. eecyan@ustc.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular disease (CVD) remains the leading cause of global mortality, highlighting the need for scalable, continuous, and contactless diagnostics. Traditional electrocardiogram (ECG) systems, though essential for detecting cardiac abnormalities, are constrained by contact-based, intermittent measurements. In this work, we introduce CardioRadar, a clinically validated radar-based system for contactless 12-lead ECG monitoring. Compact custom radar hardware captures chest micro-motions induced by cardiac activity, while data-driven inverse modeling reconstructs electrical signals from mechanical motion. Validated in 6974 individuals across diverse clinical settings, CardioRadar achieves a mean correlation of 0.75 (median: 0.77), RMSE of 0.09 mV (median: 0.07 mV), and inter-beat interval error of 23.39 ms (median: 5.60 ms) compared to ground-truth ECG. It also reliably detects arrhythmias and supports continuous overnight monitoring. CardioRadar represents a transformative, low-cost solution for equitable, long-term cardiovascular care.

Identifiers

PMID42032310
PMCPMC13055045

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.