Evidence map›Paper›PMID 42243083›Full record

ArticleNature communications2026

Wearable, broadband auscultation patch with cantilever pressure transducer for remote healthcare monitoring.

Tran Bach Dang, Chi Cong Nguyen, Seung Yun Heo, Thanh Vinh Nguyen, Nicholas Tong, Michael G Ruppert, Thanh An Truong, Michael Listyawan, James Davies, Sinuo Zhao and 7 more

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

17 authors.

Tran Bach DangSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia.
Chi Cong NguyenSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia. cong.c.nguyen@unsw.edu.au.ORCID 0000-0002-8113-5163
Seung Yun HeoHemorhythmics Inc., Evanston, IL, USA.
Thanh Vinh NguyenFormfactor Inc., Livermore, CA, USA.
Nicholas TongSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia.
Michael G RuppertCentre for Audio, Acoustics and Vibration, University of Technology Sydney, Ultimo, NSW, Australia.ORCID 0000-0003-2286-4929
Thanh An TruongSchool of Engineering and Built Environment, Griffith University, Gold Coast Campus, QLD, Australia.
Michael ListyawanSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia.
James DaviesGraduate School of Biomedical Engineering, UNSW Sydney, Kensington Campus, Sydney, NSW, Australia.ORCID 0000-0001-7987-2378
Sinuo ZhaoSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia.
Quang Anh NguyenSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia.
Nhat Minh DoanSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia.
Anthony SunjayaSchool of Population Health, Faculty of Medicine, UNSW, Sydney, NSW, Australia.
Tracie BarberSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia.
Nigel H LovellGraduate School of Biomedical Engineering, UNSW Sydney, Kensington Campus, Sydney, NSW, Australia.ORCID 0000-0003-1637-1079
Thanh Nho DoGraduate School of Biomedical Engineering, UNSW Sydney, Kensington Campus, Sydney, NSW, Australia.
Hoang-Phuong PhanSchool of Mechanical & Manufacturing Engineering, UNSW Sydney, Kensington, NSW, Australia. hp.phan@unsw.edu.au.ORCID 0000-0002-1724-5667

Funding

Department of Education and Training | Australian Research Council (ARC) DP230101312Department of Education and Training | Australian Research Council (ARC) FT240100203Department of Health | National Health and Medical Research Council (NHMRC) 2037040
6 · The paper itself

Abstract

Flexible and wearable devices employing acoustic sensors have emerged as promising alternatives for continuous monitoring of physiological mechano-acoustic signals during daily activities, offering distinct advantages over conventional rigid stethoscopes. However, the limited low-frequency sensitivity of commercial MEMS acoustic sensors constrains their ability to accurately capture vital physiological signals. Here, we present a wireless, flexible auscultation patch (AusculPatch) that overcomes these limitations by employing a highly sensitive cantilever pressure transducer (CPT). The combination of a narrow airgap in CPT together with the ultra-low mass of the nanothin cantilever enables precise measurement across a broad acoustic frequency range (0.2 Hz to over 10 kHz), allowing the detection of multiple physiological mechano-acoustic signals, including pulse waves, Korotkoff sounds, cardiac signals, respiration patterns, and vocalizations. The single-chip architecture simplifies circuitry, enabling a lightweight design ( ~ 3.2 g), compact form factor (20×47×3.5 mm), and low power consumption (4.5 mW), making AusculPatch an ideal platform for continuous wear for cardiorespiratory monitoring and potentially sleep quality assessment. These features represent a significant advance in the development of low-cost and multifunctional wearable devices capable of multi-site auscultation for home-based wellness monitoring as well as Artificial Intelligence (AI)-assisted diagnosis and Human-Machine Interaction (HMI) applications.

Indexed as

AuscultationTransducers, PressureWearable Electronic DevicesAcousticsEquipment DesignHumansMonitoring, PhysiologicRemote Patient MonitoringWireless Technology

Identifiers

PMID42243083
PMCPMC13237169

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.