Evidence map›Paper›PMID 42185285›Full record

ArticleNature communications2026

Measuring multi-site pulse transit time with an AI-enabled mmWave radar.

Jiangyifei Zhu, Kuang Yuan, Akarsh Prabhakara, Yunzhi Li, Gongwei Wang, Kelly Michaelsen, Justin Chan, Swarun Kumar

Abstract read
In one paragraph

Article in Nature communications, 2026. 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

8 authors.

Jiangyifei Zhu *Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0009-0002-3970-7591
Kuang Yuan *Department of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.ORCID 0000-0003-3901-7056
Akarsh PrabhakaraDepartment of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA.
Yunzhi LiDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
Gongwei WangDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA.
Kelly MichaelsenDepartment of Anesthesiology & Pain Medicine, University of Washington, Seattle, WA, USA.ORCID 0000-0003-3472-1335
Justin ChanDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. justinchan@cmu.edu.ORCID 0000-0002-1471-6187
Swarun KumarDepartment of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. swarun@cmu.edu.ORCID 0000-0002-5398-5347

Funding

Validating novel sleep sensors and devices in older adults with Alzheimer's diseaseP30AG073107 · NIA · UNIVERSITY OF MASSACHUSETTS AMHERST · PI Benjamin M. Marlin · 2021 to 2026
$32.0M
NIA NIH HHS P30 AG073107NSF 2106921, 2030154, 2007786, 1942902, 2111751
6 · The paper itself

Abstract

Pulse Transit Time (PTT) is a measure of arterial stiffness and a physiological marker associated with cardiovascular function, with an inverse relationship to diastolic blood pressure (DBP). We present an AI-enabled mmWave system for contactless multi-site PTT measurement using a single radar. By leveraging radar beamforming and deep learning algorithms our system simultaneously measures PTT and estimates diastolic blood pressure at multiple sites. The system was evaluated across three physiological pathways - heart-to-radial artery, heart-to-carotid artery, and mastoid area-to-radial artery - achieving correlation coefficients of 0.75-0.86 compared to contact-based reference sensors for measuring PTT. Furthermore, the system demonstrated correlation coefficients of 0.90-0.91 for estimating DBP, and achieved a mean error of -0.62-0.06 mmHg and standard deviation of 4.54-5.20 mmHg, meeting the FDA's AAMI guidelines for non-invasive blood pressure monitors. These results suggest that our proposed system has the potential to provide a non-invasive measure of cardiovascular health across multiple regions of the body.

Indexed as

Blood Pressure DeterminationPulse Wave AnalysisRadarAlgorithmsBlood PressureCarotid ArteriesHumansRadial ArteryVascular Stiffness

Identifiers

PMID42185285
PMCPMC13201791

What OpenQuestion holds

Textmetadata
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.